Official [AQLM](https://arxiv.org/abs/2401.06118) quantization of `meta-llama/Llama-2-13b-hf`. For this quantization, we used 1 codebook of 16 bits. Selected evaluation results for this and other models: | Model | AQLM scheme | WikiText 2 PPL | Model size, Gb | Hub link | |------------|-------------|----------------|----------------|--------------------------------------------------------------------------| | Llama-2-7b | 1x16 | 5.92 | 2.4 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-2Bit-1x16-hf) | | Llama-2-7b | 2x8 | 6.69 | 2.2 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-2Bit-2x8-hf) | | Llama-2-7b | 8x8 | 6.61 | 2.2 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-2Bit-8x8-hf) | | Llama-2-13b (THIS) | 1x16 | 5.22 | 4.1 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-13b-AQLM-2Bit-1x16-hf)| | Llama-2-70b| 1x16 | 3.83 | 18.8 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-70b-AQLM-2Bit-1x16-hf)| | Llama-2-70b| 2x8 | 4.21 | 18.2 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-70b-AQLM-2Bit-2x8-hf) | | Mixtral-8x7b| 1x16 | 3.35 | 12.6 | [Link](https://huggingface.co/ISTA-DASLab/Mixtral-8x7b-AQLM-2Bit-1x16-hf)| | Mixtral-8x7b-Instruct| 1x16 | - | 12.6 | [Link](https://huggingface.co/ISTA-DASLab/Mixtral-8x7B-Instruct-v0_1-AQLM-2Bit-1x16-hf)| 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).