Update README.md

README.md

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