Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
sail/Sailor-7B - GGUF
This repo contains GGUF format model files for sail/Sailor-7B.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
Prompt template
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
Sailor-7B-Q2_K.gguf | Q2_K | 3.104 GB | smallest, significant quality loss - not recommended for most purposes |
Sailor-7B-Q3_K_S.gguf | Q3_K_S | 3.569 GB | very small, high quality loss |
Sailor-7B-Q3_K_M.gguf | Q3_K_M | 3.919 GB | very small, high quality loss |
Sailor-7B-Q3_K_L.gguf | Q3_K_L | 4.218 GB | small, substantial quality loss |
Sailor-7B-Q4_0.gguf | Q4_0 | 4.512 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Sailor-7B-Q4_K_S.gguf | Q4_K_S | 4.543 GB | small, greater quality loss |
Sailor-7B-Q4_K_M.gguf | Q4_K_M | 4.767 GB | medium, balanced quality - recommended |
Sailor-7B-Q5_0.gguf | Q5_0 | 5.399 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Sailor-7B-Q5_K_S.gguf | Q5_K_S | 5.399 GB | large, low quality loss - recommended |
Sailor-7B-Q5_K_M.gguf | Q5_K_M | 5.531 GB | large, very low quality loss - recommended |
Sailor-7B-Q6_K.gguf | Q6_K | 6.342 GB | very large, extremely low quality loss |
Sailor-7B-Q8_0.gguf | Q8_0 | 8.212 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/Sailor-7B-GGUF --include "Sailor-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/Sailor-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
- Downloads last month
- 230
Model tree for tensorblock/Sailor-7B-GGUF
Datasets used to train tensorblock/Sailor-7B-GGUF
Evaluation results
- EM (3-Shot) on XQuAD-Thaiself-reported57.880
- F1 (3-Shot) on XQuAD-Thaiself-reported71.060
- EM (3-Shot) on TyDiQA-Indonesianself-reported60.530
- F1 (3-Shot) on TyDiQA-Indonesianself-reported75.420
- EM (3-Shot) on XQuAD-Vietnameseself-reported53.810
- F1 (3-Shot) on XQuAD-Vietnameseself-reported74.620
- EM (3-Shot) on XCOPA-Thaiself-reported59.000
- EM (3-Shot) on XCOPA-Indonesianself-reported72.200
- EM (3-Shot) on XCOPA-Vietnameseself-reported72.200
- EM (3-Shot) on M3Exam-Thaiself-reported30.000