metadata
language:
- en
license: other
library_name: transformers
datasets:
- teknium/OpenHermes-2.5
- LDJnr/Capybara
- Intel/orca_dpo_pairs
- argilla/distilabel-capybara-dpo-7k-binarized
pipeline_tag: text-generation
tags:
- TensorBlock
- GGUF
base_model: vilm/Quyen-SE-v0.1
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
vilm/Quyen-SE-v0.1 - GGUF
This repo contains GGUF format model files for vilm/Quyen-SE-v0.1.
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 |
---|---|---|---|
Quyen-SE-v0.1-Q2_K.gguf | Q2_K | 0.298 GB | smallest, significant quality loss - not recommended for most purposes |
Quyen-SE-v0.1-Q3_K_S.gguf | Q3_K_S | 0.333 GB | very small, high quality loss |
Quyen-SE-v0.1-Q3_K_M.gguf | Q3_K_M | 0.350 GB | very small, high quality loss |
Quyen-SE-v0.1-Q3_K_L.gguf | Q3_K_L | 0.364 GB | small, substantial quality loss |
Quyen-SE-v0.1-Q4_0.gguf | Q4_0 | 0.395 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Quyen-SE-v0.1-Q4_K_S.gguf | Q4_K_S | 0.397 GB | small, greater quality loss |
Quyen-SE-v0.1-Q4_K_M.gguf | Q4_K_M | 0.407 GB | medium, balanced quality - recommended |
Quyen-SE-v0.1-Q5_0.gguf | Q5_0 | 0.453 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Quyen-SE-v0.1-Q5_K_S.gguf | Q5_K_S | 0.453 GB | large, low quality loss - recommended |
Quyen-SE-v0.1-Q5_K_M.gguf | Q5_K_M | 0.459 GB | large, very low quality loss - recommended |
Quyen-SE-v0.1-Q6_K.gguf | Q6_K | 0.515 GB | very large, extremely low quality loss |
Quyen-SE-v0.1-Q8_0.gguf | Q8_0 | 0.665 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/Quyen-SE-v0.1-GGUF --include "Quyen-SE-v0.1-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/Quyen-SE-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'