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---
library_name: transformers
tags:
- TensorBlock
- GGUF
base_model: hyper-accel/tiny-random-exaone
---
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## hyper-accel/tiny-random-exaone - GGUF
This repo contains GGUF format model files for [hyper-accel/tiny-random-exaone](https://huggingface.co/hyper-accel/tiny-random-exaone).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4882](https://github.com/ggml-org/llama.cpp/commit/be7c3034108473beda214fd1d7c98fd6a7a3bdf5).
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## Prompt template
```
[|system|]{system_prompt}[|endofturn|]
[|user|]{prompt}
[|assistant|]
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [tiny-random-exaone-Q2_K.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q2_K.gguf) | Q2_K | 0.135 GB | smallest, significant quality loss - not recommended for most purposes |
| [tiny-random-exaone-Q3_K_S.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q3_K_S.gguf) | Q3_K_S | 0.147 GB | very small, high quality loss |
| [tiny-random-exaone-Q3_K_M.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q3_K_M.gguf) | Q3_K_M | 0.148 GB | very small, high quality loss |
| [tiny-random-exaone-Q3_K_L.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q3_K_L.gguf) | Q3_K_L | 0.150 GB | small, substantial quality loss |
| [tiny-random-exaone-Q4_0.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q4_0.gguf) | Q4_0 | 0.165 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [tiny-random-exaone-Q4_K_S.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q4_K_S.gguf) | Q4_K_S | 0.165 GB | small, greater quality loss |
| [tiny-random-exaone-Q4_K_M.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q4_K_M.gguf) | Q4_K_M | 0.166 GB | medium, balanced quality - recommended |
| [tiny-random-exaone-Q5_0.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q5_0.gguf) | Q5_0 | 0.181 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [tiny-random-exaone-Q5_K_S.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q5_K_S.gguf) | Q5_K_S | 0.181 GB | large, low quality loss - recommended |
| [tiny-random-exaone-Q5_K_M.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q5_K_M.gguf) | Q5_K_M | 0.182 GB | large, very low quality loss - recommended |
| [tiny-random-exaone-Q6_K.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q6_K.gguf) | Q6_K | 0.199 GB | very large, extremely low quality loss |
| [tiny-random-exaone-Q8_0.gguf](https://huggingface.co/tensorblock/tiny-random-exaone-GGUF/blob/main/tiny-random-exaone-Q8_0.gguf) | Q8_0 | 0.256 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/tiny-random-exaone-GGUF --include "tiny-random-exaone-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/tiny-random-exaone-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
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