Create model card (#1)
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Co-authored-by: Yozh <justheuristic@users.noreply.huggingface.co>
README.md
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---
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library_name: transformers
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tags:
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- llama
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- facebook
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- meta
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- llama-2
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- conversational
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- text-generation-inference
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---
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An official quantization of [meta-llama/Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b) using [PV-Tuning](https://arxiv.org/abs/2405.14852) on top of [AQLM](https://arxiv.org/abs/2401.06118).
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For this quantization, we used 1 codebook of 16 bits for groups of 8 weights.
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| Model | AQLM scheme | WikiText 2 PPL | Model size, Gb | Hub link |
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|------------|-------------|----------------|----------------|--------------------------------------------------------------------------|
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| Llama-2-7b (this) | 1x16 | 5.68 | 2.4 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-PV-2Bit-1x16-hf) |
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| Llama-2-7b | 2x8 | 5.90 | 2.2 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-PV-2Bit-2x8-hf) |
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| Llama-2-13b| 1x16 | 5.05 | 4.1 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-13b-AQLM-PV-2Bit-1x16-hf)|
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| Llama-2-70b| 1x16 | 3.78 | 18.8 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-70b-AQLM-PV-2Bit-1x16-hf)|
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The 1x16g16 (1-bit) models are on the way, as soon as we update the inference lib with their respective kernels.
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To learn more about the inference, as well as the information on how to quantize models yourself, please refer to the [official GitHub repo](https://github.com/Vahe1994/AQLM).
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The original code for PV-Tuning can be found in the [AQLM@pv-tuning](https://github.com/Vahe1994/AQLM/tree/pv-tuning) branch.
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