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@@ -6,12 +6,13 @@ Selected evaluation results for this and other models:
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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 | 1x16 | 6.31 | 2.4 | [Link](https://huggingface.co/BlackSamorez/Llama-2-7b-AQLM-2Bit-1x16-hf) |
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- | Llama-2-7b | 2x8 | 7.98 | 2.2 | [Link](https://huggingface.co/BlackSamorez/Llama-2-7b-AQLM-2Bit-2x8-hf) |
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- | Llama-2-7b | 8x8 | 7.83 | 2.2 | [Link](https://huggingface.co/BlackSamorez/Llama-2-7b-AQLM-2Bit-8x8-hf) |
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  | Llama-2-13b| 1x16 | 5.41 | 4.1 | [Link](https://huggingface.co/BlackSamorez/Llama-2-13b-AQLM-2Bit-1x16-hf)|
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  | Llama-2-70b| 1x16 | 3.96 | 18.8 | [Link](https://huggingface.co/BlackSamorez/Llama-2-70b-AQLM-2Bit-1x16-hf)|
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  | Llama-2-70b| 2x8 | 4.83 | 18.2 | [Link](https://huggingface.co/BlackSamorez/Llama-2-70b-AQLM-2Bit-2x8-hf) |
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  | Mixtral-8x7b (THIS)| 1x16 | 4.37 | 12.6 | [Link](https://huggingface.co/BlackSamorez/Mixtral-8x7b-AQLM-2Bit-1x16-hf)|
 
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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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  | Model | AQLM scheme | WikiText 2 PPL | Model size, Gb | Hub link |
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  |------------|-------------|----------------|----------------|--------------------------------------------------------------------------|
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+ | Llama-2-7b | 1x16 | 5.92 | 2.4 | [Link](https://huggingface.co/BlackSamorez/Llama-2-7b-AQLM-2Bit-1x16-hf) |
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+ | Llama-2-7b | 2x8 | 6.69 | 2.2 | [Link](https://huggingface.co/BlackSamorez/Llama-2-7b-AQLM-2Bit-2x8-hf) |
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+ | Llama-2-7b | 8x8 | 6.61 | 2.2 | [Link](https://huggingface.co/BlackSamorez/Llama-2-7b-AQLM-2Bit-8x8-hf) |
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  | Llama-2-13b| 1x16 | 5.41 | 4.1 | [Link](https://huggingface.co/BlackSamorez/Llama-2-13b-AQLM-2Bit-1x16-hf)|
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  | Llama-2-70b| 1x16 | 3.96 | 18.8 | [Link](https://huggingface.co/BlackSamorez/Llama-2-70b-AQLM-2Bit-1x16-hf)|
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  | Llama-2-70b| 2x8 | 4.83 | 18.2 | [Link](https://huggingface.co/BlackSamorez/Llama-2-70b-AQLM-2Bit-2x8-hf) |
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  | Mixtral-8x7b (THIS)| 1x16 | 4.37 | 12.6 | [Link](https://huggingface.co/BlackSamorez/Mixtral-8x7b-AQLM-2Bit-1x16-hf)|
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+ | Mixtral-8x7b-Instruct| 1x16 | - | 12.6 | [Link](https://huggingface.co/BlackSamorez/Mixtral-8x7B-Instruct-v0_1-AQLM-2Bit-1x16-hf)|
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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).