From ad27225a8f2c02ab776f657ed9703a4480381613 Mon Sep 17 00:00:00 2001 From: Yue Sun Date: Fri, 24 Jul 2026 12:23:37 +0800 Subject: [PATCH] Point report fetch at main/site and stamp winml-cli version The upstream site-src branch was merged into main under site/. Fetch site/e2e_model_coverage_result/examples_compatibility_report.html from main, decouple the upstream file name from the published model_accuracy_report.html so the docs URL stays stable, and stamp the placeholder version string with the winml-cli version from pyproject.toml. Refresh the README source docs and the published report. --- docs/reports/README.md | 12 +- docs/reports/download_report.py | 44 ++- docs/reports/model_accuracy_report.html | 465 ++++++++++++------------ 3 files changed, 282 insertions(+), 239 deletions(-) diff --git a/docs/reports/README.md b/docs/reports/README.md index 2e5f595a2..9b0457d14 100644 --- a/docs/reports/README.md +++ b/docs/reports/README.md @@ -18,9 +18,13 @@ documentation site, plus the script used to refresh it. ## Source The report is generated in the private `gim-home/ModelKitArtifacts` repo and -lives at `e2e_model_coverage_result/model_accuracy_report.html` on its -`site-src` branch. The page embeds all of its data inline, so only this one -file needs to be published — no JSON or other assets are fetched at runtime. +lives at `site/e2e_model_coverage_result/examples_compatibility_report.html` on +its `main` branch. It is published here under the stable name +`model_accuracy_report.html` so the docs URL never changes. The page embeds all +of its data inline, so only this one file needs to be published — no JSON or +other assets are fetched at runtime. The upstream report carries a placeholder +version string; `download_report.py` stamps it with the winml-cli version from +`pyproject.toml` on fetch. ## Refreshing the report @@ -40,7 +44,7 @@ script: python docs/reports/download_report.py --account ``` -This sparse-clones the `site-src` branch of the private artifacts repo and copies +This sparse-clones the `main` branch of the private artifacts repo and copies the single report file. Use `--out ` to write elsewhere. The script only fetches — it does not commit or push. diff --git a/docs/reports/download_report.py b/docs/reports/download_report.py index 8105d2827..3a342bd89 100644 --- a/docs/reports/download_report.py +++ b/docs/reports/download_report.py @@ -9,8 +9,10 @@ This script downloads the single, self-contained coverage report HTML page so it can be published on the winml-cli documentation site. It pulls the file -directly from the `site-src` branch of gim-home/ModelKitArtifacts; it does -not download release assets. +directly from the `main` branch of gim-home/ModelKitArtifacts (under `site/`); +it does not download release assets. The upstream report carries a placeholder +version string, which this script stamps with the winml-cli version read from +pyproject.toml. The report, this script, and the README live together in `docs/reports/` on `main`. mkdocs publishes the HTML as a static asset under each docs version; @@ -39,18 +41,33 @@ import argparse import os +import re import shutil import subprocess import sys import tempfile from pathlib import Path +import tomllib + SOURCE_REPO = "gim-home/ModelKitArtifacts" -SOURCE_BRANCH = "site-src" -SOURCE_FILE = "e2e_model_coverage_result/model_accuracy_report.html" -REPORT_FILENAME = SOURCE_FILE.rsplit("/", 1)[-1] +SOURCE_BRANCH = "main" +SOURCE_FILE = "site/e2e_model_coverage_result/examples_compatibility_report.html" +# The upstream file name differs from the published name; publish under a +# stable name so the docs URL (.../reports/model_accuracy_report.html) never +# changes. +REPORT_FILENAME = "model_accuracy_report.html" DEFAULT_OUT = Path(__file__).resolve().parent / REPORT_FILENAME +# winml-cli version source of truth. The upstream report ships a placeholder +# version string that is stamped with this value on fetch. +PYPROJECT = Path(__file__).resolve().parents[2] / "pyproject.toml" + + +def _winml_cli_version() -> str: + """Read the winml-cli version from pyproject.toml (stdlib only).""" + with PYPROJECT.open("rb") as f: + return tomllib.load(f)["project"]["version"] def _get_clone_url(account: str | None = None) -> str: @@ -156,9 +173,24 @@ def main() -> None: ) sys.exit(1) + version = _winml_cli_version() + html, replaced = re.subn( + r"(WinML CLI )\d+\.\d+\.\d+", + rf"\g<1>{version}", + src_file.read_text(encoding="utf-8"), + ) + if replaced: + print(f"Stamped report with WinML CLI {version}.") + else: + print( + "WARNING: version placeholder 'WinML CLI x.y.z' not found in " + "the report; published as-is.", + file=sys.stderr, + ) + out_path = args.out.resolve() out_path.parent.mkdir(parents=True, exist_ok=True) - shutil.copy2(src_file, out_path) + out_path.write_text(html, encoding="utf-8") size_kb = out_path.stat().st_size / 1024 print(f"Done. Wrote {out_path} ({size_kb:.0f} KB).") diff --git a/docs/reports/model_accuracy_report.html b/docs/reports/model_accuracy_report.html index d5593c98b..392f9ae67 100644 --- a/docs/reports/model_accuracy_report.html +++ b/docs/reports/model_accuracy_report.html @@ -55,6 +55,8 @@ .ep-chip.selected{border-color:var(--accent);box-shadow:0 0 0 2px var(--accent);background:var(--accent-soft)} .ep-chip .chip-name{font-weight:600;font-size:14px;margin-bottom:4px;display:flex;align-items:center;gap:5px;color:var(--pass)} .ep-chip .chip-stats{color:var(--text);font-weight:600} +.ep-chip .chip-date{color:var(--text-dim);font-size:11px;font-weight:400;margin-top:3px} +.ep-chip .chip-runs{color:var(--accent,#0f6cbd);font-size:11px;font-weight:600;margin-top:3px;white-space:nowrap} .legend-note{background:var(--bg2);border-bottom:1px solid var(--border);padding:10px 28px;display:flex;align-items:flex-start;gap:16px;flex-wrap:wrap;font-size:13px;color:var(--text-dim)} .legend-note code{font-family:'Cascadia Code','Consolas',monospace;font-size:12px;background:var(--bg3);border:1px solid var(--border);border-radius:3px;padding:1px 5px;color:var(--text)} .legend-note strong{color:var(--text)} @@ -187,16 +189,16 @@

Model Accuracy Report

- +
WinML CLI 0.2.0  ·  Windows ML 2.0
-
Total Models
199
Total Model · Task Pairs
226
Compatible on All 10 EPs
69
Accuracy-Tested Models
71
Accuracy Pass All 10 EPs
52
+
Total Model · Task Pairs
230
Compat Pass All 10 EPs
141
Accuracy Pass All 10 EPs
48
-
✓ DML GPU
175/226 (77.4%)
✓ MIGraph GPU
182/226 (80.5%)
✓ MLAS CPU
177/226 (78.3%)
✓ OV NPU
160/226 (70.8%)
✓ OV GPU
131/226 (58.0%)
✓ OV CPU
173/226 (76.5%)
✓ QNN NPU
145/226 (64.2%)
✓ QNN GPU
127/226 (56.2%)
✓ TRTRTX GPU
171/226 (75.7%)
✓ VitisAI NPU
172/226 (76.1%)
+
✓ DML GPU
169/230 (73.5%)
✓ MIGraphX GPU
174/230 (75.7%)
✓ MLAS CPU
169/230 (73.5%)
✓ OV NPU
164/230 (71.3%)
✓ OV GPU
167/230 (72.6%)
✓ OV CPU
166/230 (72.2%)
✓ QNN NPU
159/230 (69.1%)
✓ QNN GPU
153/230 (66.5%)
✓ TRTRTX GPU
170/230 (73.9%)
✓ VitisAI NPU
165/230 (71.7%)
@@ -232,316 +234,321 @@

Model Accuracy Report

Each tile is split by | into Compatibility (left) and Accuracy (right):
  • Compatibility — the WinML CLI built the model for that execution provider and completed the winml perf benchmark without errors or timeout (unquantized model).
  • Accuracy — the model's output matches the PyTorch baseline within the metric threshold. A — accuracy half means that pair was not accuracy-tested.
Hover any tile for the metric, task and per-precision results.
✓ pass✗ fail▼ accuracy regression◷ timed out∅ not applicable— no data / not tested
- + - - - - - - - - - - + + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - - - + - - - - - - - - + + + + + + + + - - - - - - - - + + + + + + + + + + + + + + + + + + - - - - - - - + + + + + + + + + + + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + - - - - - + + - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - - + + - - - + - + - - - - + + + - - - + - - + + + + + + + + + + - + + + + + + + + + + + + + + + + + + + + + + + + + - + + + + - + + + + + + + - + - - + + + + - - - + + + + + + + + + + + + + + + + + - - - - - - - - - - - - - + + + + - - + + - - - - - - - - - - - - - - - - - - - - - - + + - - - - + + + + + - - - - + + - - - - - - - - - + + - - - - + + - - - - - + + + + + + + + + + - - - + + + - - - - - - - - - - - - - - - - + - - + + - - + +
ModelTaskDML GPUMIGraph GPUMLAS CPUOV NPUOV GPUOV CPUQNN NPUQNN GPUTRTRTX GPUVitisAI NPU
Comp|AccComp|AccComp|AccComp|AccComp|AccComp|AccComp|AccComp|AccComp|AccComp|Acc
ModelTaskDML GPUMIGraphX GPUMLAS CPUOV NPUOV GPUOV CPUQNN NPUQNN GPUTRTRTX GPUVitisAI NPU
Comp|AccComp|AccComp|AccComp|AccComp|AccComp|AccComp|AccComp|AccComp|AccComp|Acc
▼sentence-transformers5 models · 12 pairs12/12|9/912/12|9/912/12|9/912/12|9/912/12|9/912/12|9/911/12|9/912/12|9/912/12|9/912/12|9/9
all-MiniLM-L6-v2feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
all-MiniLM-L6-v2sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
all-mpnet-base-v2feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
all-mpnet-base-v2sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
multi-qa-mpnet-base-dot-v1feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
multi-qa-mpnet-base-dot-v1sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
paraphrase-multilingual-MiniLM-L12-v2feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
paraphrase-multilingual-MiniLM-L12-v2sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
paraphrase-multilingual-mpnet-base-v2sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼sentence-transformers5 models · 12 pairs12/12|9/912/12|9/912/12|9/912/12|9/912/12|9/912/12|9/912/12|9/912/12|9/912/12|9/912/12|9/9
all-MiniLM-L6-v2feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
all-MiniLM-L6-v2sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
all-mpnet-base-v2feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
all-mpnet-base-v2sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
multi-qa-mpnet-base-dot-v1feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
multi-qa-mpnet-base-dot-v1sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
paraphrase-multilingual-MiniLM-L12-v2feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
paraphrase-multilingual-MiniLM-L12-v2sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
paraphrase-multilingual-mpnet-base-v2sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
all-mpnet-base-v2fill-mask✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
multi-qa-mpnet-base-dot-v1fill-mask✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
paraphrase-multilingual-mpnet-base-v2feature-extraction✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—
▼BAAI6 models · 10 pairs10/10|7/710/10|7/710/10|7/710/10|7/710/10|7/710/10|7/710/10|7/710/10|7/710/10|7/710/10|7/7
bge-base-en-v1.5feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-base-en-v1.5sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-large-en-v1.5sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-m3feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-m3sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-small-en-v1.5feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-small-en-v1.5sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
paraphrase-multilingual-mpnet-base-v2feature-extraction✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼BAAI6 models · 10 pairs10/10|7/710/10|7/710/10|7/710/10|7/710/10|7/710/10|7/710/10|7/79/10|6/79/10|7/710/10|7/7
bge-base-en-v1.5feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-base-en-v1.5sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-large-en-v1.5sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-m3sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-small-en-v1.5feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-small-en-v1.5sentence-similarity✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bge-large-en-v1.5feature-extraction✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
bge-m3feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓
bge-reranker-basetext-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
bge-reranker-v2-m3text-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼google-bert4 models · 6 pairs6/6|5/56/6|5/56/6|5/56/6|5/56/6|5/56/6|5/56/6|5/56/6|5/56/6|5/56/6|5/5
bert-base-multilingual-casedfeature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-base-multilingual-casedfill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-base-multilingual-uncasedfill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-base-uncasedfill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-large-uncased-whole-word-masking-finetuned-squadquestion-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-base-multilingual-casedmasked-lm✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼facebook19 models · 21 pairs17/21|6/618/21|6/618/21|6/616/21|6/69/21|6/618/21|6/615/21|6/69/21|4/617/21|6/618/21|6/6
convnext-tiny-224image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
dino-vitb16image-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
dino-vits16image-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
dinov2-smallimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
dinov2-baseimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓
dinov2-largeimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓
bart-large-cnnsummarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
bart-large-mnlitext-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
bge-reranker-v2-m3text-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
▼facebook19 models · 21 pairs10/21|7/811/21|7/810/21|7/810/21|6/811/21|7/811/21|7/812/21|6/89/21|4/811/21|7/811/21|6/8
convnext-tiny-224image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
dino-vitb16image-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
dino-vits16image-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
dinov2-smallimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bart-large-cnnsummarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
detr-resnet-50feature-extraction✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
detr-resnet-50object-detection✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓✓|▼✓|✗✓|✓✓|▼
dinov2-baseimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓
dinov2-largeimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓
bart-large-mnlitext-classification✗|✗✗|✗✗|✗✗|✗✗|✗✗|✗✗|✗✗|✗✗|✗✗|✗
bart-large-mnlizero-shot-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
detr-resnet-50feature-extraction✓|—✓|—✓|—✗|—✗|—✓|—✗|—✓|—✓|—✓|—
detr-resnet-50object-detection✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
dinov2-giantimage-feature-extraction✗|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
dinov2-giantimage-feature-extraction✗|—✓|—✗|—✓|—✓|—✓|—✗|—✗|—✓|—✓|—
nllb-200-distilled-600Mtranslation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
nougat-baseimage-to-text✓|—✓|—✓|—✗|—✓|—✓|—✓|—✗|—✓|—✓|—
sam-vit-basemask-generation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
sam-vit-hugemask-generation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
sam-vit-largemask-generation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
sam2-hiera-largemask-generation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
sam2.1-hiera-largemask-generation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
sam2.1-hiera-smallmask-generation✓|—✓|—✓|—✓|—✗|—✓|—✗|—✗|—✓|—✓|—
sam2.1-hiera-tinymask-generation✓|—✓|—✓|—✓|—✗|—✓|—✗|—✗|—✓|—✓|—
nougat-baseimage-to-text✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
sam-vit-basemask-generation✗|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—✗|—✗|—
sam-vit-hugemask-generation✗|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—✗|—✗|—
sam-vit-largemask-generation✗|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—✗|—✗|—
sam2-hiera-largemask-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
sam2.1-hiera-largemask-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
sam2.1-hiera-smallmask-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
sam2.1-hiera-tinymask-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼distilbert4 models4/4|4/44/4|4/44/4|4/44/4|4/44/4|4/44/4|4/44/4|4/44/4|4/44/4|4/44/4|4/4
distilbert-base-cased-distilled-squadquestion-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
distilbert-base-uncasedfill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
distilbert-base-uncased-distilled-squadquestion-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
distilbert-base-uncased-finetuned-sst-2-englishtext-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼microsoft28 models23/28|10/1023/28|9/1023/28|10/1015/28|10/1020/28|9/1023/28|10/1014/28|10/1011/28|7/1023/28|9/1022/28|10/10
resnet-18image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
resnet-50image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
swin-large-patch4-window7-224image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
distilbert-base-cased-distilled-squadquestion-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
distilbert-base-uncasedfill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
distilbert-base-uncased-distilled-squadquestion-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
distilbert-base-uncased-finetuned-sst-2-englishtext-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼nvidia6 models6/6|3/56/6|3/56/6|5/55/6|3/56/6|3/56/6|3/55/6|3/56/6|3/56/6|3/56/6|3/5
segformer-b1-finetuned-ade-512-512image-segmentation✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
segformer-b2-finetuned-ade-512-512image-segmentation✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
segformer-b5-finetuned-ade-640-640image-segmentation✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
segformer-b0-finetuned-ade-512-512image-segmentation✓|✗✓|✗✓|✓✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗
segformer-b0-finetuned-cityscapes-1024-1024image-segmentation✓|✗✓|✗✓|✓✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗
segformer-b5-finetuned-cityscapes-1024-1024image-segmentation✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—✓|—
▼deepset3 models3/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/3
bert-large-uncased-whole-word-masking-squad2question-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
roberta-base-squad2question-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
tinyroberta-squad2question-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼microsoft28 models23/28|9/1223/28|8/1223/28|10/1223/28|9/1223/28|8/1223/28|9/1222/28|7/1221/28|4/1223/28|9/1222/28|9/12
resnet-18image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
resnet-50image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
beit-base-patch16-224-pt22k-ft22kimage-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
llmlingua-2-xlm-roberta-large-meetingbanktoken-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
rad-dinoimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓
swinv2-tiny-patch4-window16-256image-classification✓|✓✓|▼✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
trocr-base-handwrittenimage-to-text✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✗|✓✓|✓✓|✓
trocr-base-printedimage-to-text✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✗|✓✓|✓✓|✓
trocr-large-handwrittenimage-to-text✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✗|✓✓|✓✓|✓
deberta-xlarge-mnlitext-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—
rad-dinoimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|▼✓|✓✓|✓
swin-large-patch4-window7-224image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓✓|✓
swinv2-tiny-patch4-window16-256image-classification✓|✓✓|▼✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
table-transformer-detectionobject-detection✓|✗✓|✗✓|✓✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗
table-transformer-structure-recognitionobject-detection✓|✗✓|✗✓|▼✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗
table-transformer-structure-recognition-v1.1-allobject-detection✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
tapex-basetable-question-answering✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
tapex-base-finetuned-wikisqltable-question-answering✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
tapex-base-finetuned-wtqtable-question-answering✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
tapex-largetable-question-answering✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
tapex-large-finetuned-tabfacttable-question-answering✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
tapex-large-finetuned-wikisqltable-question-answering✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
tapex-large-finetuned-wtqtable-question-answering✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
tapex-large-sql-executiontable-question-answering✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
trocr-base-handwrittenimage-to-text✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓✓|✗✓|✓✓|✓
trocr-base-printedimage-to-text✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓
trocr-large-handwrittenimage-to-text✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓
trocr-large-printedimage-to-text✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓
deberta-xlarge-mnlitext-classification✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✗|✗✗|✗✓|✗✗|◷
llmlingua-2-xlm-roberta-large-meetingbanktoken-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—
Phi-4-multimodal-instructvisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
speecht5_ttstext-to-speech✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
table-transformer-detectionobject-detection✓|✓✓|✓✓|✓✓|✓✗|✗✓|✓✓|✓✓|✗✓|✗✓|✓
table-transformer-structure-recognitionobject-detection✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
table-transformer-structure-recognition-v1.1-allobject-detection✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
tapex-basetable-question-answering✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
tapex-base-finetuned-wikisqltable-question-answering✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
tapex-base-finetuned-wtqtable-question-answering✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
tapex-largetable-question-answering✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
tapex-large-finetuned-tabfacttable-question-answering✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
tapex-large-finetuned-wikisqltable-question-answering✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
tapex-large-finetuned-wtqtable-question-answering✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
tapex-large-sql-executiontable-question-answering✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
trocr-large-printedimage-to-text✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✗|✓✗|▼✓|✓✓|✓
VibeVoice-ASR-HFaudio-text-to-text✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
VibeVoice-Realtime-0.5Btext-to-speech✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
xclip-base-patch32video-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼deepset3 models3/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/33/3|3/3
bert-large-uncased-whole-word-masking-squad2question-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
roberta-base-squad2question-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
tinyroberta-squad2question-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼FacebookAI4 models3/4|3/44/4|4/44/4|4/44/4|4/44/4|4/44/4|3/44/4|4/44/4|3/44/4|4/44/4|4/4
roberta-basefill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
roberta-largefill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
xlm-roberta-basefill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
xlm-roberta-largefill-mask✗|◷✓|✓✓|✓✓|✓✓|✓✓|◷✓|✓✓|▼✓|✓✓|✓
▼Intel4 models · 5 pairs5/5|2/25/5|2/25/5|2/25/5|2/24/5|2/24/5|2/24/5|2/25/5|2/25/5|2/24/5|2/2
bert-base-uncased-mrpcfeature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-base-uncased-mrpctext-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
dpt-hybrid-midasdepth-estimation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
dpt-largedepth-estimation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
zoedepth-nyu-kittidepth-estimation✓|—✓|—✓|—✓|—✗|—✗|—✗|—✓|—✓|—✗|—
▼openai5 models · 9 pairs6/9|6/66/9|5/66/9|6/66/9|6/66/9|6/66/9|6/63/9|6/66/9|4/66/9|6/66/9|3/6
clip-vit-base-patch16feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
clip-vit-base-patch32feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
clip-vit-base-patch32zero-shot-image-classification✓|✓✓|—✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼
clip-vit-base-patch16zero-shot-image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✗|✓✓|✓✓|✓✓|✓
clip-vit-base-patch16zero-shot-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
clip-vit-base-patch32zero-shot-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
clip-vit-large-patch14zero-shot-image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✗|✓✓|▼✓|✓✓|▼
clip-vit-large-patch14-336zero-shot-image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✗|✓✓|▼✓|✓✓|▼
gpt-oss-20btext-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼google10 models · 12 pairs7/12|2/29/12|2/27/12|2/27/12|2/25/12|2/27/12|2/27/12|2/22/12|2/25/12|2/28/12|2/2
vit-base-patch16-224image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
vit-base-patch16-224-in21kimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼google10 models · 12 pairs8/12|3/49/12|3/48/12|2/48/12|2/48/12|4/48/12|2/46/12|2/47/12|2/49/12|4/49/12|3/4
vit-base-patch16-224image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
vit-base-patch16-224-in21kimage-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
flan-t5-base✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
flan-t5-basesummarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
flan-t5-basetranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
siglip-base-patch16-224zero-shot-image-classification✓|✓✓|✓✓|✗✓|▼✓|✓✓|✗✓|✗✓|✗✓|✓✓|✓
deplotvisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
flan-t5-base✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
flan-t5-basesummarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
flan-t5-basetranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
madlad400-3b-mttranslation✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✓|—
pegasus-xsumsummarization✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—
madlad400-3b-mttranslation✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✓|—✓|—
pegasus-xsumsummarization✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—✓|—
pix2struct-ai2d-basevisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
pix2struct-docvqa-basevisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
siglip-base-patch16-224zero-shot-image-classification✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
siglip-so400m-patch14-384zero-shot-image-classification✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
▼laion2 models · 4 pairs3/4|3/33/4|2/33/4|2/33/4|3/33/4|3/33/4|2/33/4|3/33/4|3/33/4|3/33/4|2/3
CLIP-ViT-B-32-laion2B-s34B-b79Kfeature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
CLIP-ViT-B-32-laion2B-s34B-b79Kzero-shot-image-classification✓|✓✓|—✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼
CLIP-ViT-H-14-laion2B-s32B-b79Kzero-shot-image-classification✓|✓✓|✓✓|◷✓|✓✓|✓✓|◷✓|✓✓|✓✓|✓✓|✓
siglip-so400m-patch14-384zero-shot-image-classification✓|✗✓|✗✓|✗✓|▼✓|✓✓|✗✗|✗✓|✗✓|✓✓|✗
▼google-bert4 models · 6 pairs6/6|5/56/6|5/56/6|3/56/6|5/56/6|5/56/6|5/56/6|5/56/6|2/56/6|5/56/6|5/5
bert-base-multilingual-casedfeature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-large-uncased-whole-word-masking-finetuned-squadquestion-answering✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-base-multilingual-casedfill-mask✓|✓✓|✓✓|✗✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓
bert-base-multilingual-casedmasked-lm✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
bert-base-multilingual-uncasedfill-mask✓|✓✓|✓✓|✗✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓
bert-base-uncasedfill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓
▼openai5 models · 9 pairs6/9|6/66/9|6/66/9|6/66/9|6/66/9|4/66/9|6/66/9|6/66/9|3/66/9|6/66/9|3/6
clip-vit-base-patch16feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
clip-vit-base-patch32feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
clip-vit-base-patch16zero-shot-image-classification✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓✓|✓✓|✓✓|✓
clip-vit-base-patch32zero-shot-image-classification✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓✓|✗✓|✓✓|✗
clip-vit-large-patch14zero-shot-image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|▼
clip-vit-large-patch14-336zero-shot-image-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|▼
clip-vit-base-patch16zero-shot-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
clip-vit-base-patch32zero-shot-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
gpt-oss-20btext-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼Intel4 models · 5 pairs5/5|2/55/5|2/55/5|2/55/5|2/55/5|2/54/5|2/54/5|2/55/5|2/55/5|2/54/5|2/5
bert-base-uncased-mrpcfeature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-base-uncased-mrpctext-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
dpt-hybrid-midasdepth-estimation✓|∅✓|∅✓|∅✓|∅✓|✗✓|✗✓|◷✓|✗✓|∅✓|∅
dpt-largedepth-estimation✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅
zoedepth-nyu-kittidepth-estimation✓|∅✓|∅✓|∅✓|∅✓|∅✗|✗✗|✗✓|✗✓|∅✗|◷
▼laion2 models · 4 pairs3/4|2/33/4|2/32/4|2/33/4|3/33/4|2/33/4|2/32/4|2/32/4|1/33/4|3/33/4|1/3
CLIP-ViT-B-32-laion2B-s34B-b79Kfeature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
CLIP-ViT-B-32-laion2B-s34B-b79Kzero-shot-image-classification✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓✓|✗✓|✓✓|✗
CLIP-ViT-B-32-laion2B-s34B-b79Kzero-shot-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
CLIP-ViT-H-14-laion2B-s32B-b79Kzero-shot-image-classification✓|✗✓|✗✗|✗✓|✓✓|✓✓|✗✗|✗✗|✗✓|✓✓|✗
▼apple2 models1/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/1
mobilevit-smallimage-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
mobilevit-smallimage-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
DepthPro-hfdepth-estimation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼Babelscape1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
wikineural-multilingual-nertoken-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼cardiffnlp1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
twitter-roberta-base-sentiment-latesttext-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼dbmdz1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
bert-large-cased-finetuned-conll03-englishtoken-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼dima8061 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
fairface_age_image_detectionimage-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-large-cased-finetuned-conll03-englishtoken-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼dslim1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
bert-base-NERtoken-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bert-base-NERtoken-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼Isotonic1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
distilbert_finetuned_ai4privacy_v2token-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼joeddav2 models1/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/1
xlm-roberta-large-xnlizero-shot-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
bart-large-mnli-yahoo-answerszero-shot-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
distilbert_finetuned_ai4privacy_v2token-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼mattmdjaga1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
segformer_b2_clothesimage-segmentation✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼ProsusAI1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
finberttext-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼rizvandwiki1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
gender-classificationimage-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
finberttext-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼w11wo1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
indonesian-roberta-base-posp-taggertoken-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼cross-encoder3 models3/3|—3/3|—3/3|—3/3|—2/3|—3/3|—3/3|—3/3|—3/3|—3/3|—
indonesian-roberta-base-posp-taggertoken-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼google-t54 models · 7 pairs5/7|—7/7|—5/7|—5/7|—5/7|—5/7|—4/7|—4/7|—7/7|—7/7|—
t5-basesummarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
t5-basetranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
t5-smallsummarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
t5-smalltranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
t5-3bsummarization✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✓|—✓|—
t5-3btranslation✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✓|—✓|—
t5-largesummarization✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—✓|—
▼cross-encoder3 models3/3|0/13/3|0/13/3|0/13/3|0/13/3|0/13/3|0/13/3|0/13/3|0/13/3|0/13/3|0/1
ms-marco-MiniLM-L4-v2text-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
ms-marco-MiniLM-L6-v2text-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
nli-deberta-v3-smallzero-shot-classification✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
nli-deberta-v3-smallzero-shot-classification✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|✗✓|∅✓|∅✓|∅
▼depth-anything3 models3/3|0/33/3|1/33/3|0/33/3|0/33/3|0/33/3|0/33/3|0/33/3|1/33/3|1/33/3|1/3
Depth-Anything-V2-Base-hfdepth-estimation✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅
Depth-Anything-V2-Large-hfdepth-estimation✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅
Depth-Anything-V2-Small-hfdepth-estimation✓|∅✓|✓✓|∅✓|∅✓|∅✓|∅✓|◷✓|✓✓|✓✓|✓
▼FacebookAI4 models3/4|3/44/4|3/44/4|1/44/4|3/44/4|3/44/4|2/43/4|3/43/4|0/43/4|3/44/4|3/4
roberta-basefill-mask✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓
roberta-largefill-mask✓|✓✓|✓✓|✗✓|✓✓|✓✓|✗✓|✓✓|✗✓|✓✓|✓
xlm-roberta-basefill-mask✓|✓✓|✓✓|✗✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓
xlm-roberta-largefill-mask✗|✗✓|✗✓|✗✓|✗✓|✗✓|✗✗|✗✗|✗✗|✗✓|✗
▼Helsinki-NLP5 models3/5|—3/5|—3/5|—3/5|—3/5|—3/5|—3/5|—3/5|—3/5|—3/5|—
opus-mt-es-entranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
opus-mt-nl-entranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
opus-mt-tr-entranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
opus-mt-en-rutranslation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
opus-mt-fr-entranslation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼LiheYoung3 models3/3|0/32/3|0/23/3|0/33/3|0/33/3|0/33/3|0/33/3|0/33/3|0/32/3|0/22/3|0/2
depth-anything-large-hfdepth-estimation✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅
depth-anything-small-hfdepth-estimation✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|◷✓|✗✓|∅✓|∅
depth-anything-base-hfdepth-estimation✓|∅✗|—✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✗|—✗|—
▼MoritzLaurer4 models4/4|0/44/4|0/44/4|0/44/4|0/44/4|0/44/4|0/44/4|0/44/4|0/44/4|0/42/4|0/4
mDeBERTa-v3-base-mnli-xnlizero-shot-classification✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|✗✓|✗✓|∅✓|✗
mDeBERTa-v3-base-xnli-multilingual-nli-2mil7zero-shot-classification✓|∅✓|∅✓|∅✓|∅✓|∅✓|∅✓|✗✓|✗✓|∅✓|✗
DeBERTa-v3-large-mnli-fever-anli-ling-wanlizero-shot-classification✓|∅✓|∅✓|✗✓|∅✓|∅✓|✗✓|✗✓|✗✓|∅✗|◷
deberta-v3-large-zeroshot-v2.0zero-shot-classification✓|∅✓|∅✓|✗✓|∅✓|∅✓|✗✓|✗✓|✗✓|∅✗|◷
▼StanfordAIMI2 models2/2|1/12/2|1/12/2|1/12/2|1/12/2|1/12/2|1/12/2|1/12/2|0/12/2|1/12/2|1/1
dinov2-base-xray-224image-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓
dinov2-base-xray-224image-feature-extraction✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓
stanford-deidentifier-basetoken-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼timm2 models2/2|—2/2|—2/2|—2/2|—2/2|—2/2|—2/2|—2/2|—2/2|—2/2|—
mobilenetv3_small_100.lamb_in1kimage-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
repghostnet_200.in1kimage-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼AdamCodd1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
vit-base-nsfw-detectorimage-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼ahotrod1 model1/1|1/11/1|0/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
electra_large_discriminator_squad2_512question-answering✓|✓✓|▼✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
electra_large_discriminator_squad2_512question-answering✓|✓✓|▼✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼amunchet1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
rorshark-vit-baseimage-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼Babelscape1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|0/11/1|1/11/1|1/11/1|1/1
wikineural-multilingual-nertoken-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓✓|✓
▼dima8061 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|0/11/1|1/11/1|1/11/1|1/1
fairface_age_image_detectionimage-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓✓|✓
▼Falconsai1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
nsfw_image_detectionimage-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼fashn-ai1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
fashn-human-parserimage-segmentation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼hustvl1 model1/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/1
yolos-smallobject-detection✓|▼✓|▼✓|▼✓|▼✓|▼✓|▼✓|▼✓|▼✓|▼✓|▼
yolos-smallobject-detection✓|▼✓|▼✓|▼✓|▼✓|▼✓|▼✓|✗✓|✗✓|▼✓|▼
▼Jean-Baptiste1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
camembert-ner-with-datestoken-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼kredor1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
punctuate-alltoken-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼jonathandinu1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
face-parsingimage-segmentation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼lxyuan1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
distilbert-base-multilingual-cased-sentiments-studentzero-shot-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼mixedbread-ai1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
mxbai-rerank-xsmall-v1text-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼monologg1 model1/1|1/11/1|0/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
koelectra-small-v2-distilled-korquad-384question-answering✓|✓✓|▼✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼patrickjohncyh1 model1/1|1/11/1|0/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|0/1
fashion-clipzero-shot-image-classification✓|✓✓|—✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼
koelectra-small-v2-distilled-korquad-384question-answering✓|✓✓|▼✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼obi1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
deid_roberta_i2b2token-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼patrickjohncyh1 model1/1|1/11/1|1/11/1|1/11/1|0/11/1|1/11/1|1/11/1|0/11/1|0/11/1|1/11/1|0/1
fashion-clipzero-shot-image-classification✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓✓|▼✓|✗✓|✓✓|✗
▼rizvandwiki1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|0/11/1|1/11/1|1/11/1|1/1
gender-classificationimage-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✗✓|✓✓|✓✓|✓
▼Salesforce5 models1/5|1/11/5|0/11/5|1/11/5|1/11/5|0/11/5|1/11/5|1/11/5|0/11/5|1/11/5|1/1
blip-image-captioning-baseimage-to-text✓|✓✓|✗✓|✓✓|✓✓|✗✓|✓✓|✓✓|✗✓|✓✓|✓
blip-vqa-basevisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
blip2-flan-t5-xlvisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
blip2-opt-2.7bvisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
blip2-opt-2.7b-cocovisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼sshleifer1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
distilbart-cnn-12-6summarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼TahaDouaji1 model1/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/1
detr-doc-table-detectionobject-detection✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗
▼tau1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
splinter-basequestion-answering✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—✓|—
▼valentinafeve1 model1/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|0/11/1|1/11/1|1/11/1|0/1
yolos-fashionpediaobject-detection✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|▼✓|✓✓|✓✓|▼
▼nvidia6 models6/6|3/36/6|3/36/6|3/35/6|3/30/6|3/36/6|3/34/6|3/36/6|3/36/6|3/36/6|3/3
segformer-b1-finetuned-ade-512-512image-segmentation✓|✓✓|✓✓|✓✓|✓✗|✓✓|✓✓|✓✓|✓✓|✓✓|✓
segformer-b2-finetuned-ade-512-512image-segmentation✓|✓✓|✓✓|✓✓|✓✗|✓✓|✓✓|✓✓|✓✓|✓✓|✓
segformer-b5-finetuned-ade-640-640image-segmentation✓|✓✓|✓✓|✓✓|✓✗|✓✓|✓✗|✓✓|✓✓|✓✓|✓
segformer-b0-finetuned-ade-512-512image-segmentation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
segformer-b0-finetuned-cityscapes-1024-1024image-segmentation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
segformer-b5-finetuned-cityscapes-1024-1024image-segmentation✓|—✓|—✓|—✗|—✗|—✓|—✗|—✓|—✓|—✓|—
▼cardiffnlp1 model1/1|1/11/1|1/11/1|1/10/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
twitter-roberta-base-sentiment-latesttext-classification✓|✓✓|✓✓|✓✗|✓✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼mattmdjaga1 model1/1|1/11/1|1/11/1|1/11/1|1/10/1|1/11/1|1/11/1|1/11/1|1/11/1|1/11/1|1/1
segformer_b2_clothesimage-segmentation✓|✓✓|✓✓|✓✓|✓✗|✓✓|✓✓|✓✓|✓✓|✓✓|✓
▼timpal0l1 model1/1|1/11/1|0/11/1|1/11/1|0/11/1|1/11/1|1/11/1|0/11/1|1/11/1|1/11/1|1/1
mdeberta-v3-base-squad2question-answering✓|✓✓|▼✓|✓✓|▼✓|✓✓|✓✓|✗✓|✓✓|✓✓|✓
▼valentinafeve1 model1/1|0/11/1|0/11/1|1/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/11/1|0/1
yolos-fashionpediaobject-detection✓|✗✓|✗✓|✓✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗
▼ai-forever1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
Real-ESRGAN✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼alibaba-damo1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
mgp-str-baseimage-to-text✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼breezedeus1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
pix2text-mfrimage-to-text✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼buildborderless1 model1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—0/1|—1/1|—1/1|—1/1|—
CommunityForensics-DeepfakeDet-ViTimage-classification✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—✓|—
▼buildborderless1 model1/1|—1/1|—1/1|—0/1|—0/1|—0/1|—0/1|—1/1|—1/1|—1/1|—
CommunityForensics-DeepfakeDet-ViTimage-classification✓|—✓|—✓|—✗|—✗|—✗|—✗|—✓|—✓|—✓|—
▼dandelin1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
vilt-b32-finetuned-vqavisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼depth-anything3 models3/3|—3/3|—3/3|—3/3|—0/3|—3/3|—3/3|—3/3|—3/3|—3/3|—
Depth-Anything-V2-Base-hfdepth-estimation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
Depth-Anything-V2-Large-hfdepth-estimation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
Depth-Anything-V2-Small-hfdepth-estimation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
▼fashn-ai1 model1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
fashn-human-parserimage-segmentation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
▼flaviagiammarino1 model1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—0/1|—1/1|—1/1|—
medsam-vit-basemask-generation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
▼google-t54 models · 7 pairs5/7|—7/7|—5/7|—5/7|—5/7|—5/7|—5/7|—0/7|—0/7|—7/7|—
t5-3bsummarization✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✓|—
t5-3btranslation✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✓|—
t5-basesummarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
t5-basetranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
t5-largesummarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
t5-smallsummarization✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
t5-smalltranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—
▼Helsinki-NLP5 models3/5|—3/5|—3/5|—3/5|—3/5|—3/5|—3/5|—0/5|—3/5|—3/5|—
opus-mt-en-rutranslation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
opus-mt-es-entranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—
opus-mt-fr-entranslation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
opus-mt-nl-entranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—
opus-mt-tr-entranslation✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—
▼flaviagiammarino1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—1/1|—0/1|—0/1|—0/1|—
medsam-vit-basemask-generation✗|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—✗|—✗|—
▼hi-wesley1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
gemma3-vision-encoderimage-feature-extraction✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼internlm1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
internlm-xcomposer2d5-7bvisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼intfloat1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—
multilingual-e5-largesentence-similarity✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—
▼jonathandinu1 model1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
face-parsingimage-segmentation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
▼kha-white1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—0/1|—0/1|—1/1|—1/1|—
manga-ocr-baseimage-to-text✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—✓|—
▼joeddav2 models1/2|1/11/2|1/11/2|1/11/2|1/11/2|1/11/2|1/10/2|0/11/2|1/11/2|1/11/2|1/1
bart-large-mnli-yahoo-answerszero-shot-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
xlm-roberta-large-xnlizero-shot-classification✓|✓✓|✓✓|✓✓|✓✓|✓✓|✓✗|✗✓|✓✓|✓✓|✓
▼kha-white1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—1/1|—
manga-ocr-baseimage-to-text✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—
▼knkarthick1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
MEETING_SUMMARYsummarization✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼LiheYoung3 models2/3|—2/3|—2/3|—2/3|—0/3|—2/3|—2/3|—2/3|—2/3|—2/3|—
depth-anything-base-hfdepth-estimation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
depth-anything-large-hfdepth-estimation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
depth-anything-small-hfdepth-estimation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
▼kredor1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—1/1|—
punctuate-alltoken-classification✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—
▼Marqo1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
marqo-fashionSigLIPzero-shot-image-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼mixedbread-ai1 model1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
mxbai-rerank-xsmall-v1text-classification✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
▼MoritzLaurer4 models4/4|—4/4|—4/4|—4/4|—0/4|—4/4|—4/4|—4/4|—4/4|—2/4|—
DeBERTa-v3-large-mnli-fever-anli-ling-wanlizero-shot-classification✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✗|—
deberta-v3-large-zeroshot-v2.0zero-shot-classification✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✗|—
mDeBERTa-v3-base-mnli-xnlizero-shot-classification✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
mDeBERTa-v3-base-xnli-multilingual-nli-2mil7zero-shot-classification✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
▼moussaKam1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
mbarthezsummarization✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼naver-clova-ix2 models2/2|—2/2|—2/2|—1/2|—2/2|—2/2|—0/2|—0/2|—2/2|—2/2|—
donut-baseimage-to-text✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
donut-base-finetuned-cord-v2image-to-text✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—✓|—
donut-baseimage-to-text✓|—✓|—✓|—✗|—✓|—✓|—✗|—✗|—✓|—✓|—
donut-base-finetuned-cord-v2image-to-text✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—✓|—
▼nlpconnect1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—0/1|—0/1|—1/1|—0/1|—
vit-gpt2-image-captioningimage-to-text✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✓|—✗|—
▼obi1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—1/1|—
deid_roberta_i2b2token-classification✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—
▼oliverguhr1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—1/1|—
fullstop-punctuation-multilang-largetoken-classification✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—
▼oliverguhr1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—
fullstop-punctuation-multilang-largetoken-classification✓|—✓|—✓|—✓|—✓|—✓|—✓|—✗|—✓|—✓|—
▼openai-community1 model1/1|—1/1|—1/1|—0/1|—0/1|—0/1|—0/1|—0/1|—1/1|—0/1|—
gpt2text-generation✓|—✓|—✓|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—
▼PekingU3 models3/3|—2/3|—3/3|—3/3|—0/3|—3/3|—3/3|—0/3|—3/3|—3/3|—
rtdetr_r101vd_coco_o365object-detection✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
rtdetr_r50vd_coco_o365object-detection✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
rtdetr_v2_r18vdobject-detection✓|—✗|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
gpt2text-generation✓|—✓|—✓|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—
▼PaddlePaddle4 models0/2|—0/2|—0/2|—0/2|—0/2|—0/2|—2/4|—2/4|—0/2|—0/2|—
PP-OCRv5_server_detimage-to-text✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
PP-OCRv5_server_recimage-to-text✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
PP-OCRv6_medium_det_onnx/inference.onnximage-to-text∅|—∅|—∅|—∅|—∅|—∅|—✓|—✓|—∅|—∅|—
PP-OCRv6_medium_rec_onnx/inference.onnximage-to-text∅|—∅|—∅|—∅|—∅|—∅|—✓|—✓|—∅|—∅|—
▼PekingU3 models3/3|0/32/3|0/33/3|0/33/3|0/33/3|0/33/3|0/33/3|0/30/3|0/33/3|0/33/3|0/3
rtdetr_r101vd_coco_o365object-detection✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✗|✗✓|✗✓|✗
rtdetr_r50vd_coco_o365object-detection✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✓|✗✗|✗✓|✗✓|✗
rtdetr_v2_r18vdobject-detection✓|✗✗|✗✓|✗✓|✗✓|✗✓|✗✓|✗✗|✗✓|✗✓|✗
▼philschmid1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
bart-large-cnn-samsumsummarization✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼Qwen7 models1/7|—3/7|—1/7|—0/7|—0/7|—0/7|—0/7|—0/7|—2/7|—0/7|—
Qwen2.5-0.5B-Instructtext-generation✓|—✓|—✓|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—
Qwen2.5-1.5B-Instructtext-generation✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—
▼Qwen7 models1/7|—3/7|—1/7|—0/7|—0/7|—0/7|—0/7|—0/7|—0/7|—0/7|—
Qwen2.5-0.5B-Instructtext-generation✓|—✓|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
Qwen2.5-1.5B-Instructtext-generation✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
Qwen2.5-3B-Instructtext-generation✗|—✓|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
Qwen2.5-7B-Instructtext-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
Qwen3-0.6Btext-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
Qwen3-1.7Btext-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
Qwen3-8Btext-generation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼Salesforce5 models1/5|1/11/5|0/11/5|1/11/5|1/11/5|1/11/5|1/10/5|1/10/5|0/11/5|1/11/5|1/1
blip-image-captioning-baseimage-to-text✓|✓✓|▼✓|✓✓|✓✓|✓✓|✓✗|✓✗|▼✓|✓✓|✓
blip-vqa-basevisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
blip2-flan-t5-xlvisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
blip2-opt-2.7bvisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
blip2-opt-2.7b-cocovisual-question-answering✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼sshleifer1 model1/1|—1/1|—1/1|—1/1|—1/1|—1/1|—0/1|—0/1|—0/1|—1/1|—
distilbart-cnn-12-6summarization✓|—✓|—✓|—✓|—✓|—✓|—✗|—✗|—✗|—✓|—
▼TahaDouaji1 model1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—1/1|—1/1|—1/1|—
detr-doc-table-detectionobject-detection✓|—✓|—✓|—✓|—✗|—✓|—✓|—✓|—✓|—✓|—
▼timm2 models—|——|——|——|——|——|——|——|—2/2|——|—
mobilenetv3_small_100.lamb_in1kimage-classification∅|—∅|—∅|—∅|—∅|—∅|—∅|—∅|—✓|—∅|—
repghostnet_200.in1kimage-classification∅|—∅|—∅|—∅|—∅|—∅|—∅|—∅|—✓|—∅|—
▼timpal0l1 model1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—0/1|—1/1|—1/1|—1/1|—
mdeberta-v3-base-squad2question-answering✓|—✓|—✓|—✓|—✗|—✓|—✗|—✓|—✓|—✓|—
▼trl-internal-testing1 model1/1|—1/1|—1/1|—0/1|—0/1|—0/1|—0/1|—0/1|—1/1|—0/1|—
tiny-Qwen2ForCausalLM-2.5text-generation✓|—✓|—✓|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—
tiny-Qwen2ForCausalLM-2.5text-generation✓|—✓|—✓|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—
▼valhalla1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—
distilbart-mnli-12-3zero-shot-classification✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼wanglab1 model1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—0/1|—1/1|—1/1|—
medsam-vit-basemask-generation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
▼wanglab1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—1/1|—0/1|—0/1|—0/1|—
medsam-vit-basemask-generation✗|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—✗|—✗|—
▼Xenova2 models0/2|—0/2|—0/2|—0/2|—0/2|—0/2|—0/2|—0/2|—0/2|—0/2|—
paraphrase-multilingual-MiniLM-L12-v2feature-extraction✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
segformer-b0-finetuned-ade-512-512image-segmentation✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—✗|—
▼Zigeng1 model1/1|—1/1|—1/1|—1/1|—0/1|—1/1|—1/1|—0/1|—1/1|—1/1|—
SlimSAM-uniform-77mask-generation✓|—✓|—✓|—✓|—✗|—✓|—✓|—✗|—✓|—✓|—
▼Zigeng1 model0/1|—0/1|—0/1|—0/1|—0/1|—0/1|—1/1|—0/1|—0/1|—0/1|—
SlimSAM-uniform-77mask-generation✗|—✗|—✗|—✗|—✗|—✗|—✓|—✗|—✗|—✗|—
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Compatibility (build & run) across 10 execution providers for 226 model · task pairs; accuracy graded against the PyTorch baseline for 83 of them. · 69/199 models run on every EP.
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Compatibility (build & run) across 10 execution providers for 230 model · task pairs; accuracy graded against the PyTorch baseline for 110 of them. · 141/230 model · task pairs run on every EP.