metadata
license: apache-2.0
language:
- ja
- en
datasets:
- augmxnt/ultra-orca-boros-en-ja-v1
- Open-Orca/SlimOrca
- augmxnt/shisa-en-ja-dpo-v1
tags:
- TensorBlock
- GGUF
base_model: augmxnt/shisa-7b-v1
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
augmxnt/shisa-7b-v1 - GGUF
This repo contains GGUF format model files for augmxnt/shisa-7b-v1.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
<s>[INST] <<SYS>>
{system_prompt}
<</SYS>>
{prompt} [/INST]
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| shisa-7b-v1-Q2_K.gguf | Q2_K | 2.921 GB | smallest, significant quality loss - not recommended for most purposes |
| shisa-7b-v1-Q3_K_S.gguf | Q3_K_S | 3.370 GB | very small, high quality loss |
| shisa-7b-v1-Q3_K_M.gguf | Q3_K_M | 3.700 GB | very small, high quality loss |
| shisa-7b-v1-Q3_K_L.gguf | Q3_K_L | 3.982 GB | small, substantial quality loss |
| shisa-7b-v1-Q4_0.gguf | Q4_0 | 4.294 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| shisa-7b-v1-Q4_K_S.gguf | Q4_K_S | 4.323 GB | small, greater quality loss |
| shisa-7b-v1-Q4_K_M.gguf | Q4_K_M | 4.535 GB | medium, balanced quality - recommended |
| shisa-7b-v1-Q5_0.gguf | Q5_0 | 5.164 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| shisa-7b-v1-Q5_K_S.gguf | Q5_K_S | 5.164 GB | large, low quality loss - recommended |
| shisa-7b-v1-Q5_K_M.gguf | Q5_K_M | 5.288 GB | large, very low quality loss - recommended |
| shisa-7b-v1-Q6_K.gguf | Q6_K | 6.088 GB | very large, extremely low quality loss |
| shisa-7b-v1-Q8_0.gguf | Q8_0 | 7.884 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/shisa-7b-v1-GGUF --include "shisa-7b-v1-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/shisa-7b-v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'