The flower of Ares.
These are the GGUF files of the fine-tuned model. To be compiled with llama.cpp on oobabooga or VLLm.
Fine-tuned on mistralai/Mistral-7B-v0.1...my team and I reformatted many different datasets and included a small amount of private stuff to see how much we could improve mistral.
I spoke to it personally for about an hour, and I believe we need to work on our format for the private dataset a bit more, but other than that, it turned out great. I will be uploading it to open llm evaluations, today.
Provided files
Name | Quant method | Bits | Size | Max RAM required | Use case |
---|---|---|---|---|---|
Q2_K Tiny | Q2_K | 2 | 2.7 GB | 4.7 GB | smallest, significant quality loss - not recommended for most purposes |
Q3_K_M | Q3_K_M | 3 | 3.52 GB | 5.52 GB | very small, high quality loss |
Q4_0 | Q4_0 | 4 | 4.11 GB | 6.11 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Q4_K_M | Q4_K_M | 4 | 4.37 GB | 6.37 GB | medium, balanced quality - recommended |
Q5_0 | Q5_0 | 5 | 5 GB | 7 GB | legacy; large, balanced quality |
Q5_K_M | Q5_K_M | 5 | 5.13 GB | 7.13 GB | large, balanced quality - recommended |
Q6 XL | Q6_K | 6 | 5.94 GB | 7.94 GB | very large, extremely low quality loss |
Q8 XXL | Q8_0 | 8 | 7.7 GB | 9.7 GB | very large, extremely low quality loss - not recommended |
- Uses Mistral prompt template with chat-instruct.
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