Instructions to use starkdmi/FRCRN_SE_16K_MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use starkdmi/FRCRN_SE_16K_MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir FRCRN_SE_16K_MLX starkdmi/FRCRN_SE_16K_MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Neutral wording, single-machine caveat, correct project link
Browse files
README.md
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@@ -21,17 +21,13 @@ Speech enhancement at 16 kHz. This model was converted to MLX format from
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| `model_fp32.safetensors` | 56 MB | the weights |
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| `FRCRN_SE_16K.yaml` | 614 B | upstream model configuration |
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| `weights.npz` | 110 MB | superseded
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fp32 only; no half-precision or quantized conversion is published.
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`weights.npz` predates the safetensors conversion and is kept
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`model_fp32.safetensors`.
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##
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`ModelRepository.frcrnSE16K`, which pins this repository to an exact revision and
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verifies the SHA-256 of every file it downloads. The loader reads the safetensors
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and nothing else — the YAML is provided for reference.
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| --- | ---: | --- |
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| `model_fp32.safetensors` | 56 MB | the weights |
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| `FRCRN_SE_16K.yaml` | 614 B | upstream model configuration |
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| `weights.npz` | 110 MB | superseded |
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fp32 only; no half-precision or quantized conversion is published.
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`weights.npz` predates the safetensors conversion and is kept so that anything
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already referring to it keeps working. Load `model_fp32.safetensors`.
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## Used by
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[AudioToolSwift](https://github.com/starkdmi/AudioToolSwift)
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