README.md

---
license: apache-2.0
datasets:
- Skylion007/openwebtext
- JeanKaddour/minipile
language:
- en
pipeline_tag: text-generation
inference:
  parameters:
    do_sample: true
    temperature: 0.5
    top_p: 0.5
    top_k: 50
    max_new_tokens: 250
    repetition_penalty: 1.176
base_model: Locutusque/TinyMistral-248M
tags:
- TensorBlock
- GGUF
---

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## Locutusque/TinyMistral-248M - GGUF

This repo contains GGUF format model files for [Locutusque/TinyMistral-248M](https://huggingface.co/Locutusque/TinyMistral-248M).

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 |
| -------- | ---------- | --------- | ----------- |
| [TinyMistral-248M-Q2_K.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q2_K.gguf) | Q2_K | 0.098 GB | smallest, significant quality loss - not recommended for most purposes |
| [TinyMistral-248M-Q3_K_S.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q3_K_S.gguf) | Q3_K_S | 0.112 GB | very small, high quality loss |
| [TinyMistral-248M-Q3_K_M.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q3_K_M.gguf) | Q3_K_M | 0.120 GB | very small, high quality loss |
| [TinyMistral-248M-Q3_K_L.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q3_K_L.gguf) | Q3_K_L | 0.128 GB | small, substantial quality loss |
| [TinyMistral-248M-Q4_0.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q4_0.gguf) | Q4_0 | 0.139 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [TinyMistral-248M-Q4_K_S.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q4_K_S.gguf) | Q4_K_S | 0.139 GB | small, greater quality loss |
| [TinyMistral-248M-Q4_K_M.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q4_K_M.gguf) | Q4_K_M | 0.145 GB | medium, balanced quality - recommended |
| [TinyMistral-248M-Q5_0.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q5_0.gguf) | Q5_0 | 0.164 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [TinyMistral-248M-Q5_K_S.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q5_K_S.gguf) | Q5_K_S | 0.164 GB | large, low quality loss - recommended |
| [TinyMistral-248M-Q5_K_M.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q5_K_M.gguf) | Q5_K_M | 0.167 GB | large, very low quality loss - recommended |
| [TinyMistral-248M-Q6_K.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q6_K.gguf) | Q6_K | 0.190 GB | very large, extremely low quality loss |
| [TinyMistral-248M-Q8_0.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-GGUF/blob/main/TinyMistral-248M-Q8_0.gguf) | Q8_0 | 0.246 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/TinyMistral-248M-GGUF --include "TinyMistral-248M-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/TinyMistral-248M-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```