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Add URLs to HF MLX-Community org. (#153)
* up * Add ref to MLX org on the README. * nit: language. * Standardise org name.
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@ -16,6 +16,8 @@ Some more useful examples include:
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- Bidirectional language understanding with [BERT](bert)
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- Semi-supervised learning on graph-structured data with [GCN](gcn).
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Note: You can now directly download a few converted checkpoints from the [MLX Community](https://huggingface.co/mlx-community) organisation on Hugging Face.
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## Contributing
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We are grateful for all of [our
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@ -20,10 +20,8 @@ weights you will need to request access from Meta:
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- [Request Llama v1](https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR4uf7b_fBxjY_OjhJILlKGA/viewform)
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- [Request Llama v2](https://ai.meta.com/resources/models-and-libraries/llama-downloads/)
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Alternatively, you can also download a select converted checkpoints from the
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[mlx-llama](https://huggingface.co/mlx-llama) community organisation on Hugging
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Face and skip the conversion step.
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> [!TIP]
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> Alternatively, you can also download a few converted checkpoints from the the [MLX Community](https://huggingface.co/mlx-community) organisation on Hugging Face and skip the conversion step.
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You can download the TinyLlama models directly from [Hugging
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Face](https://huggingface.co/TinyLlama).
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@ -28,6 +28,9 @@ python convert.py
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The conversion script will save the converted weights in the same location.
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> [!TIP]
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> Alternatively, you can also download a few converted checkpoints from the the [MLX Community](https://huggingface.co/mlx-community) organisation on Hugging Face and skip the conversion step.
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### Run
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Once you've converted the weights to MLX format, you can generate text with
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@ -17,6 +17,9 @@ python convert.py
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This will make the `weights.npz` file which MLX can read.
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> [!TIP]
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> Alternatively, you can also download a few converted checkpoints from the the [MLX Community](https://huggingface.co/mlx-community) organisation on Hugging Face and skip the conversion step.
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## Generate
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To generate text with the default prompt:
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