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merged 5 commits into from
Oct 16, 2025
Merged

purge HF_HUB_ENABLE_HF_TRANSFER; promote Xet #2000

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purge HF_HUB_ENABLE_HF_TRANSFER; promote Xet
Vaibhavs10 Oct 16, 2025
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Apply suggestion from @Wauplin
Vaibhavs10 Oct 16, 2025
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review.
Vaibhavs10 Oct 16, 2025
8058a66
Update docs/hub/models-downloading.md
Vaibhavs10 Oct 16, 2025
4d7dab9
Update docs/hub/models-downloading.md
Vaibhavs10 Oct 16, 2025
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4 changes: 2 additions & 2 deletions docs/hub/mlx.md
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Expand Up @@ -70,9 +70,9 @@ response = generate(model, tokenizer, prompt="hello", verbose=True)
MLX-LM supports popular LLM architectures including LLaMA, Phi-2, Mistral, and Qwen. Models other than supported ones can easily be downloaded as follows:

```py
pip install huggingface_hub hf_transfer
pip install "huggingface_hub[hf_xet]"

export HF_HUB_ENABLE_HF_TRANSFER=1
export HF_XET_HIGH_PERFORMANCE=1
hf download --local-dir <LOCAL FOLDER PATH> <USER_ID>/<MODEL_NAME>
```

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16 changes: 4 additions & 12 deletions docs/hub/models-downloading.md
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Expand Up @@ -51,18 +51,10 @@ Add your SSH public key to [your user settings](https://huggingface.co/settings/
## Faster downloads

If you are running on a machine with high bandwidth,
you can increase your download speed with [`hf_transfer`](https://github.com/huggingface/hf_transfer),
a Rust-based library developed to speed up file transfers with the Hub.
you can increase your download speed with [`hf_xet`](https://github.com/huggingface/xet-core),
a Rust-based library developed to speed up file transfers with the Hub, powered by [Xet](https://huggingface.co/docs/hub/en/xet/index).

```bash
pip install "huggingface_hub[hf_transfer]"
HF_HUB_ENABLE_HF_TRANSFER=1 hf download ...
pip install "huggingface_hub[hf_xet]"
HF_XET_HIGH_PERFORMANCE=1 hf download ...
```

> [!WARNING]
> `hf_transfer` is a power user tool!
> It is tested and production-ready,
> but it lacks user-friendly features like advanced error handling or proxies.
> For more details, please take a look at this [guide](https://huggingface.co/docs/huggingface_hub/hf_transfer).