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Locutusque/TinyMistral-248M-v2.5 - GGUF
This repo contains GGUF format model files for Locutusque/TinyMistral-248M-v2.5.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
Prompt template
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
TinyMistral-248M-v2.5-Q2_K.gguf | Q2_K | 0.105 GB | smallest, significant quality loss - not recommended for most purposes |
TinyMistral-248M-v2.5-Q3_K_S.gguf | Q3_K_S | 0.120 GB | very small, high quality loss |
TinyMistral-248M-v2.5-Q3_K_M.gguf | Q3_K_M | 0.129 GB | very small, high quality loss |
TinyMistral-248M-v2.5-Q3_K_L.gguf | Q3_K_L | 0.137 GB | small, substantial quality loss |
TinyMistral-248M-v2.5-Q4_0.gguf | Q4_0 | 0.149 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
TinyMistral-248M-v2.5-Q4_K_S.gguf | Q4_K_S | 0.149 GB | small, greater quality loss |
TinyMistral-248M-v2.5-Q4_K_M.gguf | Q4_K_M | 0.156 GB | medium, balanced quality - recommended |
TinyMistral-248M-v2.5-Q5_0.gguf | Q5_0 | 0.176 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
TinyMistral-248M-v2.5-Q5_K_S.gguf | Q5_K_S | 0.176 GB | large, low quality loss - recommended |
TinyMistral-248M-v2.5-Q5_K_M.gguf | Q5_K_M | 0.179 GB | large, very low quality loss - recommended |
TinyMistral-248M-v2.5-Q6_K.gguf | Q6_K | 0.204 GB | very large, extremely low quality loss |
TinyMistral-248M-v2.5-Q8_0.gguf | Q8_0 | 0.264 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/TinyMistral-248M-v2.5-GGUF --include "TinyMistral-248M-v2.5-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/TinyMistral-248M-v2.5-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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Model tree for tensorblock/TinyMistral-248M-v2.5-GGUF
Base model
Locutusque/TinyMistral-248M-v2.5Datasets used to train tensorblock/TinyMistral-248M-v2.5-GGUF
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard24.570
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard27.490
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard23.150
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard46.720
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard47.830
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard0.000
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard13.360
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard3.180
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.000
- acc_norm on GPQA (0-shot)Open LLM Leaderboard0.110