metadata
license: apache-2.0
datasets:
- hyokwan/famili
language:
- ko
metrics:
- accuracy
library_name: transformers
pipeline_tag: text-generation
tags:
- finance
- TensorBlock
- GGUF
base_model: hyokwan/familidata
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
hyokwan/familidata - GGUF
This repo contains GGUF format model files for hyokwan/familidata.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
### System:
{system_prompt}
### User:
{prompt}
### Assistant:
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
familidata-Q2_K.gguf | Q2_K | 4.003 GB | smallest, significant quality loss - not recommended for most purposes |
familidata-Q3_K_S.gguf | Q3_K_S | 4.665 GB | very small, high quality loss |
familidata-Q3_K_M.gguf | Q3_K_M | 5.196 GB | very small, high quality loss |
familidata-Q3_K_L.gguf | Q3_K_L | 5.651 GB | small, substantial quality loss |
familidata-Q4_0.gguf | Q4_0 | 6.072 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
familidata-Q4_K_S.gguf | Q4_K_S | 6.119 GB | small, greater quality loss |
familidata-Q4_K_M.gguf | Q4_K_M | 6.462 GB | medium, balanced quality - recommended |
familidata-Q5_0.gguf | Q5_0 | 7.397 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
familidata-Q5_K_S.gguf | Q5_K_S | 7.397 GB | large, low quality loss - recommended |
familidata-Q5_K_M.gguf | Q5_K_M | 7.598 GB | large, very low quality loss - recommended |
familidata-Q6_K.gguf | Q6_K | 8.805 GB | very large, extremely low quality loss |
familidata-Q8_0.gguf | Q8_0 | 11.404 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/familidata-GGUF --include "familidata-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/familidata-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'