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README.md

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+---
+library_name: transformers
+tags:
+- llama
+- facebook
+- meta
+- llama-2
+- conversational
+- text-generation-inference
+---
+
+A 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) quantization
+
+
+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                                                                 |
+|------------|-------------|----------------|----------------|--------------------------------------------------------------------------|
+| Llama-2-7b (this) | 1x16g8        | 5.68          | 2.4            | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-PV-2Bit-1x16-hf) |
+| Llama-2-7b | 2x8g8         | 5.90          | 2.2            | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-PV-2Bit-2x8-hf)  |
+| Llama-2-13b| 1x16g8        | 5.05           | 4.1            | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-13b-AQLM-PV-2Bit-1x16-hf)|
+| Llama-2-70b| 1x16g8        | 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).
+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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