Instructions to use FastVideo/FastH3-Omni-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use FastVideo/FastH3-Omni-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download FastVideo/FastH3-Omni-MLX --local-dir FastH3-Omni-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
bench: include prompts in results bundle
Browse files- bench/run_matrix.py +7 -0
bench/run_matrix.py
CHANGED
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@@ -762,6 +762,13 @@ def orchestrate(args: argparse.Namespace) -> int:
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"quant_gemm": args.quant_gemm, "m5_sweep": args.m5_sweep}
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out.mkdir(parents=True, exist_ok=True)
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write_receipt(out, args, software, data, weights, settings)
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exit_code = 0
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lock = GpuLock(args.lock_dir, args.steal_stale_lock)
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# SIGINT is explicit: it is ignored by default when launched as a background job (nohup, agents).
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"quant_gemm": args.quant_gemm, "m5_sweep": args.m5_sweep}
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out.mkdir(parents=True, exist_ok=True)
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write_receipt(out, args, software, data, weights, settings)
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# Ship the exact prompts/conditions with the results so the bundle is self-describing.
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prompts_out = out / "prompts"
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prompts_out.mkdir(exist_ok=True)
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for name in ("index.json", "index.csv"):
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source = Path(args.data_root) / "prompts" / name
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if source.is_file():
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shutil.copy2(source, prompts_out / name)
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exit_code = 0
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lock = GpuLock(args.lock_dir, args.steal_stale_lock)
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# SIGINT is explicit: it is ignored by default when launched as a background job (nohup, agents).
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