metadata
license: mit
license_link: https://huggingface.co/microsoft/phi-1_5/resolve/main/LICENSE
language:
- en
pipeline_tag: text-generation
tags:
- nlp
- code
- TensorBlock
- GGUF
base_model: microsoft/phi-1_5
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
microsoft/phi-1_5 - GGUF
This repo contains GGUF format model files for microsoft/phi-1_5.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| phi-1_5-Q2_K.gguf | Q2_K | 0.542 GB | smallest, significant quality loss - not recommended for most purposes |
| phi-1_5-Q3_K_S.gguf | Q3_K_S | 0.609 GB | very small, high quality loss |
| phi-1_5-Q3_K_M.gguf | Q3_K_M | 0.687 GB | very small, high quality loss |
| phi-1_5-Q3_K_L.gguf | Q3_K_L | 0.754 GB | small, substantial quality loss |
| phi-1_5-Q4_0.gguf | Q4_0 | 0.772 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| phi-1_5-Q4_K_S.gguf | Q4_K_S | 0.780 GB | small, greater quality loss |
| phi-1_5-Q4_K_M.gguf | Q4_K_M | 0.832 GB | medium, balanced quality - recommended |
| phi-1_5-Q5_0.gguf | Q5_0 | 0.925 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| phi-1_5-Q5_K_S.gguf | Q5_K_S | 0.925 GB | large, low quality loss - recommended |
| phi-1_5-Q5_K_M.gguf | Q5_K_M | 0.956 GB | large, very low quality loss - recommended |
| phi-1_5-Q6_K.gguf | Q6_K | 1.087 GB | very large, extremely low quality loss |
| phi-1_5-Q8_0.gguf | Q8_0 | 1.407 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/phi-1_5-GGUF --include "phi-1_5-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/phi-1_5-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'