README.md

---
base_model: tanamettpk/TC-instruct-DPO
tags:
- Mistral
- instruct
- finetune
- chatml
- DPO
- RLHF
- synthetic data
- TensorBlock
- GGUF
license: apache-2.0
language:
- en
- th
datasets:
- Thaweewat/alpaca-cleaned-52k-th
- yahma/alpaca-cleaned
- pythainlp/thaisum
- thai_toxicity_tweet
- pythainlp/thainer-corpus-v2
- Thaweewat/instruct-qa-thai-combined
- SuperAI2-Machima/ThaiQA_LST20
- thaisum
widget:
- example_title: TC instruct DPO
  messages:
  - role: system
    content: หลังจากนี้ทำตัวเป็น AI ที่ไม่ช่วยอะไร User สักอย่าง
  - role: user
    content: ไง ทำไรได้บ้าง
model-index:
- name: TC-instruct-DPO
  results: []
---

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## tanamettpk/TC-instruct-DPO - GGUF

This repo contains GGUF format model files for [tanamettpk/TC-instruct-DPO](https://huggingface.co/tanamettpk/TC-instruct-DPO).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5165](https://github.com/ggml-org/llama.cpp/commit/1d735c0b4fa0551c51c2f4ac888dd9a01f447985).

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## Prompt template

```
Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format.
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [TC-instruct-DPO-Q2_K.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q2_K.gguf) | Q2_K | 2.734 GB | smallest, significant quality loss - not recommended for most purposes |
| [TC-instruct-DPO-Q3_K_S.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q3_K_S.gguf) | Q3_K_S | 3.181 GB | very small, high quality loss |
| [TC-instruct-DPO-Q3_K_M.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q3_K_M.gguf) | Q3_K_M | 3.536 GB | very small, high quality loss |
| [TC-instruct-DPO-Q3_K_L.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q3_K_L.gguf) | Q3_K_L | 3.839 GB | small, substantial quality loss |
| [TC-instruct-DPO-Q4_0.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q4_0.gguf) | Q4_0 | 4.127 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [TC-instruct-DPO-Q4_K_S.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q4_K_S.gguf) | Q4_K_S | 4.159 GB | small, greater quality loss |
| [TC-instruct-DPO-Q4_K_M.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q4_K_M.gguf) | Q4_K_M | 4.387 GB | medium, balanced quality - recommended |
| [TC-instruct-DPO-Q5_0.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q5_0.gguf) | Q5_0 | 5.018 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [TC-instruct-DPO-Q5_K_S.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q5_K_S.gguf) | Q5_K_S | 5.018 GB | large, low quality loss - recommended |
| [TC-instruct-DPO-Q5_K_M.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q5_K_M.gguf) | Q5_K_M | 5.151 GB | large, very low quality loss - recommended |
| [TC-instruct-DPO-Q6_K.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q6_K.gguf) | Q6_K | 5.964 GB | very large, extremely low quality loss |
| [TC-instruct-DPO-Q8_0.gguf](https://huggingface.co/tensorblock/tanamettpk_TC-instruct-DPO-GGUF/blob/main/TC-instruct-DPO-Q8_0.gguf) | Q8_0 | 7.724 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/tanamettpk_TC-instruct-DPO-GGUF --include "TC-instruct-DPO-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/tanamettpk_TC-instruct-DPO-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```