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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-3 |
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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/Meta-Llama-3-70B](https://huggingface.co/meta-llama/Meta-Llama-3-70B) 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 16 weights. |
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**The 1x16g16 models require aqlm inference library v1.1.6 or newer:** |
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`pip install aqlm[gpu,cpu]>=1.1.6` |
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| Model | AQLM scheme | WikiText 2 PPL | Model size, Gb | Hub link | |
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|------------|-------------|----------------|----------------|--------------------------------------------------------------------------| |
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| meta-llama/Meta-Llama-3-8B | 1x16g8 | 6.99 | 4.1 | [Link](https://huggingface.co/ISTA-DASLab/Meta-Llama-3-8B-AQLM-PV-2Bit-1x16) | |
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| meta-llama/Meta-Llama-3-8B | 1x16g16 | 9.43 | 3.9 | [Link](https://huggingface.co/ISTA-DASLab/Meta-Llama-3-8B-AQLM-PV-1Bit-1x16) | |
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| meta-llama/Meta-Llama-3-70B | 1x16g8 | 4.57 | 21.9 | [Link](https://huggingface.co/ISTA-DASLab/Meta-Llama-3-70B-AQLM-PV-2Bit-1x16)| |
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| meta-llama/Meta-Llama-3-70B (this) | 1x16g16 | 8.67 | 13 | [Link](https://huggingface.co/ISTA-DASLab/Meta-Llama-3-70B-AQLM-PV-2Bit-1x16)| |
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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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