metadata
license: other
library_name: transformers
datasets:
- ise-uiuc/Magicoder-OSS-Instruct-75K
license_name: deepseek
pipeline_tag: text-generation
base_model: ise-uiuc/Magicoder-DS-6.7B
tags:
- TensorBlock
- GGUF
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
ise-uiuc/Magicoder-DS-6.7B - GGUF
This repo contains GGUF format model files for ise-uiuc/Magicoder-DS-6.7B.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
<｜begin▁of▁sentence｜>You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.
@@ Instruction
{prompt}
@@ Response
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Magicoder-DS-6.7B-Q2_K.gguf | Q2_K | 2.360 GB | smallest, significant quality loss - not recommended for most purposes |
| Magicoder-DS-6.7B-Q3_K_S.gguf | Q3_K_S | 2.747 GB | very small, high quality loss |
| Magicoder-DS-6.7B-Q3_K_M.gguf | Q3_K_M | 3.073 GB | very small, high quality loss |
| Magicoder-DS-6.7B-Q3_K_L.gguf | Q3_K_L | 3.351 GB | small, substantial quality loss |
| Magicoder-DS-6.7B-Q4_0.gguf | Q4_0 | 3.564 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Magicoder-DS-6.7B-Q4_K_S.gguf | Q4_K_S | 3.593 GB | small, greater quality loss |
| Magicoder-DS-6.7B-Q4_K_M.gguf | Q4_K_M | 3.802 GB | medium, balanced quality - recommended |
| Magicoder-DS-6.7B-Q5_0.gguf | Q5_0 | 4.334 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Magicoder-DS-6.7B-Q5_K_S.gguf | Q5_K_S | 4.334 GB | large, low quality loss - recommended |
| Magicoder-DS-6.7B-Q5_K_M.gguf | Q5_K_M | 4.456 GB | large, very low quality loss - recommended |
| Magicoder-DS-6.7B-Q6_K.gguf | Q6_K | 5.151 GB | very large, extremely low quality loss |
| Magicoder-DS-6.7B-Q8_0.gguf | Q8_0 | 6.671 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/Magicoder-DS-6.7B-GGUF --include "Magicoder-DS-6.7B-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/Magicoder-DS-6.7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'