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Phi-3.5-mini-instruct-GGUF

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metadata
license: mit
license_link: https://huggingface.co/microsoft/Phi-3.5-mini-instruct/resolve/main/LICENSE
language:
  - multilingual
pipeline_tag: text-generation
tags:
  - nlp
  - code
  - TensorBlock
  - GGUF
widget:
  - messages:
      - role: user
        content: Can you provide ways to eat combinations of bananas and dragonfruits?
library_name: transformers
base_model: microsoft/Phi-3.5-mini-instruct
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microsoft/Phi-3.5-mini-instruct - GGUF

This repo contains GGUF format model files for microsoft/Phi-3.5-mini-instruct.

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}<|end|>
<|user|>
{prompt}<|end|>
<|assistant|>

Model file specification

Filename Quant type File Size Description
Phi-3.5-mini-instruct-Q2_K.gguf Q2_K 1.319 GB smallest, significant quality loss - not recommended for most purposes
Phi-3.5-mini-instruct-Q3_K_S.gguf Q3_K_S 1.566 GB very small, high quality loss
Phi-3.5-mini-instruct-Q3_K_M.gguf Q3_K_M 1.821 GB very small, high quality loss
Phi-3.5-mini-instruct-Q3_K_L.gguf Q3_K_L 1.944 GB small, substantial quality loss
Phi-3.5-mini-instruct-Q4_0.gguf Q4_0 2.027 GB legacy; small, very high quality loss - prefer using Q3_K_M
Phi-3.5-mini-instruct-Q4_K_S.gguf Q4_K_S 2.038 GB small, greater quality loss
Phi-3.5-mini-instruct-Q4_K_M.gguf Q4_K_M 2.229 GB medium, balanced quality - recommended
Phi-3.5-mini-instruct-Q5_0.gguf Q5_0 2.460 GB legacy; medium, balanced quality - prefer using Q4_K_M
Phi-3.5-mini-instruct-Q5_K_S.gguf Q5_K_S 2.460 GB large, low quality loss - recommended
Phi-3.5-mini-instruct-Q5_K_M.gguf Q5_K_M 2.622 GB large, very low quality loss - recommended
Phi-3.5-mini-instruct-Q6_K.gguf Q6_K 2.920 GB very large, extremely low quality loss
Phi-3.5-mini-instruct-Q8_0.gguf Q8_0 3.782 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-3.5-mini-instruct-GGUF --include "Phi-3.5-mini-instruct-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-3.5-mini-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'