Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
HiTZ/latxa-7b-v1.2 - GGUF
This repo contains GGUF format model files for HiTZ/latxa-7b-v1.2.
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 |
---|---|---|---|
latxa-7b-v1.2-Q2_K.gguf | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes |
latxa-7b-v1.2-Q3_K_S.gguf | Q3_K_S | 2.948 GB | very small, high quality loss |
latxa-7b-v1.2-Q3_K_M.gguf | Q3_K_M | 3.298 GB | very small, high quality loss |
latxa-7b-v1.2-Q3_K_L.gguf | Q3_K_L | 3.597 GB | small, substantial quality loss |
latxa-7b-v1.2-Q4_0.gguf | Q4_0 | 3.826 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
latxa-7b-v1.2-Q4_K_S.gguf | Q4_K_S | 3.857 GB | small, greater quality loss |
latxa-7b-v1.2-Q4_K_M.gguf | Q4_K_M | 4.081 GB | medium, balanced quality - recommended |
latxa-7b-v1.2-Q5_0.gguf | Q5_0 | 4.652 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
latxa-7b-v1.2-Q5_K_S.gguf | Q5_K_S | 4.652 GB | large, low quality loss - recommended |
latxa-7b-v1.2-Q5_K_M.gguf | Q5_K_M | 4.783 GB | large, very low quality loss - recommended |
latxa-7b-v1.2-Q6_K.gguf | Q6_K | 5.529 GB | very large, extremely low quality loss |
latxa-7b-v1.2-Q8_0.gguf | Q8_0 | 7.161 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/latxa-7b-v1.2-GGUF --include "latxa-7b-v1.2-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/latxa-7b-v1.2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
- Downloads last month
- 177
Model tree for tensorblock/latxa-7b-v1.2-GGUF
Base model
HiTZ/latxa-7b-v1.2Dataset used to train tensorblock/latxa-7b-v1.2-GGUF
Evaluation results
- Accuracy (0-shot) on xstory_clozePaper65.450
- Accuracy (5-shot) on belebelePaper37.330
- Average scores (5-shot) on basque_gluePaper52.560
- Accuracy (5-shot) on eus_proficiencyPaper30.260
- Accuracy (5-shot) on eus_readingPaper25.000
- Accuracy (5-shot) on eus_triviaPaper42.160
- Accuracy (5-shot) on eus_examsPaper33.820