Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
beomi/gemma-mling-7b - GGUF
This repo contains GGUF format model files for beomi/gemma-mling-7b.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
gemma-mling-7b-Q2_K.gguf | Q2_K | 3.242 GB | smallest, significant quality loss - not recommended for most purposes |
gemma-mling-7b-Q3_K_S.gguf | Q3_K_S | 3.709 GB | very small, high quality loss |
gemma-mling-7b-Q3_K_M.gguf | Q3_K_M | 4.069 GB | very small, high quality loss |
gemma-mling-7b-Q3_K_L.gguf | Q3_K_L | 4.386 GB | small, substantial quality loss |
gemma-mling-7b-Q4_0.gguf | Q4_0 | 4.668 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
gemma-mling-7b-Q4_K_S.gguf | Q4_K_S | 4.700 GB | small, greater quality loss |
gemma-mling-7b-Q4_K_M.gguf | Q4_K_M | 4.964 GB | medium, balanced quality - recommended |
gemma-mling-7b-Q5_0.gguf | Q5_0 | 5.570 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
gemma-mling-7b-Q5_K_S.gguf | Q5_K_S | 5.570 GB | large, low quality loss - recommended |
gemma-mling-7b-Q5_K_M.gguf | Q5_K_M | 5.723 GB | large, very low quality loss - recommended |
gemma-mling-7b-Q6_K.gguf | Q6_K | 6.529 GB | very large, extremely low quality loss |
gemma-mling-7b-Q8_0.gguf | Q8_0 | 8.454 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/gemma-mling-7b-GGUF --include "gemma-mling-7b-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/gemma-mling-7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
- Downloads last month
- 17
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for tensorblock/gemma-mling-7b-GGUF
Base model
beomi/gemma-mling-7bEvaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard20.290
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard17.630
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard4.150
- acc_norm on GPQA (0-shot)Open LLM Leaderboard0.000
- acc_norm on MuSR (0-shot)Open LLM Leaderboard6.850
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard18.140