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phi-2-audio-super-GGUF

Text Generation
GGUF
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conversational
ASR
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phi-2-audio-super-GGUF / README.md
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metadata
language:
  - en
license: mit
tags:
  - convAI
  - conversational
  - ASR
  - TensorBlock
  - GGUF
license_link: https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE
widget:
  - text: Hello who are you?
    example_title: Identity
  - text: What can you do?
    example_title: Capabilities
  - text: Create a fastapi endpoint to retrieve the weather given a zip code.
    example_title: Coding
pipeline_tag: text-generation
base_model: Thytu/phi-2-audio-super
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Thytu/phi-2-audio-super - GGUF

This repo contains GGUF format model files for Thytu/phi-2-audio-super.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Prompt template 

<|endoftext|>[INST] {prompt} [/INST]

Model file specification

Filename Quant type File Size Description
phi-2-audio-super-Q2_K.gguf Q2_K 1.110 GB smallest, significant quality loss - not recommended for most purposes
phi-2-audio-super-Q3_K_S.gguf Q3_K_S 1.251 GB very small, high quality loss
phi-2-audio-super-Q3_K_M.gguf Q3_K_M 1.426 GB very small, high quality loss
phi-2-audio-super-Q3_K_L.gguf Q3_K_L 1.575 GB small, substantial quality loss
phi-2-audio-super-Q4_0.gguf Q4_0 1.602 GB legacy; small, very high quality loss - prefer using Q3_K_M
phi-2-audio-super-Q4_K_S.gguf Q4_K_S 1.619 GB small, greater quality loss
phi-2-audio-super-Q4_K_M.gguf Q4_K_M 1.738 GB medium, balanced quality - recommended
phi-2-audio-super-Q5_0.gguf Q5_0 1.933 GB legacy; medium, balanced quality - prefer using Q4_K_M
phi-2-audio-super-Q5_K_S.gguf Q5_K_S 1.933 GB large, low quality loss - recommended
phi-2-audio-super-Q5_K_M.gguf Q5_K_M 2.003 GB large, very low quality loss - recommended
phi-2-audio-super-Q6_K.gguf Q6_K 2.285 GB very large, extremely low quality loss
phi-2-audio-super-Q8_0.gguf Q8_0 2.958 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-2-audio-super-GGUF --include "phi-2-audio-super-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-2-audio-super-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'