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normistral-7b-warm-instruct

Text Generation

Norwegian Bokmål

Norwegian Nynorsk

text-generation-inference

Inference Endpoints

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davda54 commited on Jun 17

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 | Name | Quant method | Bits Per Weight | Size | Max RAM/VRAM required | Use case |
 | ---- | ---- | ---- | ---- | ---- | ----- |
-| [normistral-7b-warm-instruct.Q3_K_M.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q3_K_M.gguf) | Q3_K_M | 3.89 | 3.28 GB| 5.37 GB | very small, high quality loss |
-| [normistral-7b-warm-instruct.Q4_K_M.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q4_K_M.gguf) | Q4_K_M | 4.83 | 4.07 GB| 6.16 GB | medium, balanced quality - recommended |
-| [normistral-7b-warm-instruct.Q5_K_M.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q5_K_M.gguf) | Q5_K_M | 5.67 | 4.78 GB| 6.87 GB | large, very low quality loss - recommended |
 | [normistral-7b-warm-instruct.Q6_K.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q6_K.gguf) | Q6_K | 6.56 | 5.54 GB| 7.63 GB | very large, extremely low quality loss |
-| [normistral-7b-warm-instruct.Q8_0.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q8_0.gguf) | Q8_0 | 8.50 | 7.17 GB| 9.26 GB | very large, extremely low quality loss - not recommended |
 ### How to run from Python code

 | Name | Quant method | Bits Per Weight | Size | Max RAM/VRAM required | Use case |
 | ---- | ---- | ---- | ---- | ---- | ----- |
+| [normistral-7b-warm-instruct.Q3_K_M.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q3_K_M.gguf) | Q3_K_M | 3.89 | 3.28 GB| 5.37 GB | very small, high loss of quality |
+| [normistral-7b-warm-instruct.Q4_K_M.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q4_K_M.gguf) | Q4_K_M | 4.83 | 4.07 GB| 6.16 GB | medium, balanced quality |
+| [normistral-7b-warm-instruct.Q5_K_M.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q5_K_M.gguf) | Q5_K_M | 5.67 | 4.78 GB| 6.87 GB | large, very low quality loss |
 | [normistral-7b-warm-instruct.Q6_K.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q6_K.gguf) | Q6_K | 6.56 | 5.54 GB| 7.63 GB | very large, extremely low quality loss |
+| [normistral-7b-warm-instruct.Q8_0.gguf](https://huggingface.co/norallm/normistral-7b-warm/blob/main/normistral-7b-warm-instruct.Q8_0.gguf) | Q8_0 | 8.50 | 7.17 GB| 9.26 GB | very large, extremely low quality loss |
 ### How to run from Python code