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---
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
---
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<div style="display: flex; flex-direction: column; align-items: flex-start;">
<p style="margin-top: 0.5em; margin-bottom: 0em;">
Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
</p>
</div>
</div>
## Thytu/phi-2-audio-super - GGUF
This repo contains GGUF format model files for [Thytu/phi-2-audio-super](https://huggingface.co/Thytu/phi-2-audio-super).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
<div style="text-align: left; margin: 20px 0;">
<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
Run them on the TensorBlock client using your local machine ↗
</a>
</div>
## Prompt template
```
<|endoftext|>[INST] {prompt} [/INST]
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [phi-2-audio-super-Q2_K.gguf](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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](https://huggingface.co/tensorblock/phi-2-audio-super-GGUF/blob/main/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
```shell
pip install -U "huggingface_hub[cli]"
```
Then, downoad the individual model file the a local directory
```shell
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:
```shell
huggingface-cli download tensorblock/phi-2-audio-super-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
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