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---
library_name: transformers
tags:
- trl
- sft
- TensorBlock
- GGUF
base_model: coscotuff/SLFT_Trials
---
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## coscotuff/SLFT_Trials - GGUF
This repo contains GGUF format model files for [coscotuff/SLFT_Trials](https://huggingface.co/coscotuff/SLFT_Trials).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
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## Prompt template
```
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [SLFT_Trials-Q2_K.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q2_K.gguf) | Q2_K | 0.088 GB | smallest, significant quality loss - not recommended for most purposes |
| [SLFT_Trials-Q3_K_S.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q3_K_S.gguf) | Q3_K_S | 0.088 GB | very small, high quality loss |
| [SLFT_Trials-Q3_K_M.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q3_K_M.gguf) | Q3_K_M | 0.094 GB | very small, high quality loss |
| [SLFT_Trials-Q3_K_L.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q3_K_L.gguf) | Q3_K_L | 0.098 GB | small, substantial quality loss |
| [SLFT_Trials-Q4_0.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q4_0.gguf) | Q4_0 | 0.092 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [SLFT_Trials-Q4_K_S.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q4_K_S.gguf) | Q4_K_S | 0.102 GB | small, greater quality loss |
| [SLFT_Trials-Q4_K_M.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q4_K_M.gguf) | Q4_K_M | 0.105 GB | medium, balanced quality - recommended |
| [SLFT_Trials-Q5_0.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q5_0.gguf) | Q5_0 | 0.105 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [SLFT_Trials-Q5_K_S.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q5_K_S.gguf) | Q5_K_S | 0.110 GB | large, low quality loss - recommended |
| [SLFT_Trials-Q5_K_M.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q5_K_M.gguf) | Q5_K_M | 0.112 GB | large, very low quality loss - recommended |
| [SLFT_Trials-Q6_K.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q6_K.gguf) | Q6_K | 0.138 GB | very large, extremely low quality loss |
| [SLFT_Trials-Q8_0.gguf](https://huggingface.co/tensorblock/SLFT_Trials-GGUF/blob/main/SLFT_Trials-Q8_0.gguf) | Q8_0 | 0.145 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/SLFT_Trials-GGUF --include "SLFT_Trials-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/SLFT_Trials-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
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