metadata
base_model: AlSamCur123/Mistral-Small-InstructContinuedFine
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
- sft
- TensorBlock
- GGUF
license: apache-2.0
language:
- en
AlSamCur123/Mistral-Small-InstructContinuedFine - GGUF
This repo contains GGUF format model files for AlSamCur123/Mistral-Small-InstructContinuedFine.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
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<s>[INST] {system_prompt}
{prompt}[/INST]
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Mistral-Small-InstructContinuedFine-Q2_K.gguf | Q2_K | 8.272 GB | smallest, significant quality loss - not recommended for most purposes |
| Mistral-Small-InstructContinuedFine-Q3_K_S.gguf | Q3_K_S | 9.641 GB | very small, high quality loss |
| Mistral-Small-InstructContinuedFine-Q3_K_M.gguf | Q3_K_M | 10.757 GB | very small, high quality loss |
| Mistral-Small-InstructContinuedFine-Q3_K_L.gguf | Q3_K_L | 11.730 GB | small, substantial quality loss |
| Mistral-Small-InstructContinuedFine-Q4_0.gguf | Q4_0 | 12.569 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Mistral-Small-InstructContinuedFine-Q4_K_S.gguf | Q4_K_S | 12.660 GB | small, greater quality loss |
| Mistral-Small-InstructContinuedFine-Q4_K_M.gguf | Q4_K_M | 13.341 GB | medium, balanced quality - recommended |
| Mistral-Small-InstructContinuedFine-Q5_0.gguf | Q5_0 | 15.325 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Mistral-Small-InstructContinuedFine-Q5_K_S.gguf | Q5_K_S | 15.325 GB | large, low quality loss - recommended |
| Mistral-Small-InstructContinuedFine-Q5_K_M.gguf | Q5_K_M | 15.723 GB | large, very low quality loss - recommended |
| Mistral-Small-InstructContinuedFine-Q6_K.gguf | Q6_K | 18.253 GB | very large, extremely low quality loss |
| Mistral-Small-InstructContinuedFine-Q8_0.gguf | Q8_0 | 23.641 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/Mistral-Small-InstructContinuedFine-GGUF --include "Mistral-Small-InstructContinuedFine-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/Mistral-Small-InstructContinuedFine-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'