README.md

---
language:
- en
- zh
- id
- th
- vi
- ms
- lo
- my
- jv
- km
- su
- tl
tags:
- multilingual
- sea
- sailor
- sft
- chat
- instruction
- TensorBlock
- GGUF
widget:
- text: 如何制作烤鱼？
  example_title: Chinese
- text: How to bake fish?
  example_title: English
- text: Bagaimana cara memanggang ikan?
  example_title: Malay
- text: วิธีย่างปลา?
  example_title: Thai
- text: Bagaimana membuat bakaran ikan?
  example_title: Indonesian
- text: Làm thế nào để nướng cá?
  example_title: Vietnamese
license: apache-2.0
base_model: sail/Sailor2-20B-Chat
library_name: transformers
pipeline_tag: text-generation
---

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## sail/Sailor2-20B-Chat - GGUF

This repo contains GGUF format model files for [sail/Sailor2-20B-Chat](https://huggingface.co/sail/Sailor2-20B-Chat).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4823](https://github.com/ggml-org/llama.cpp/commit/5bbe6a9fe9a8796a9389c85accec89dbc4d91e39).

## Our projects
<table border="1" cellspacing="0" cellpadding="10">
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    <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
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  <th>
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## Prompt template

```
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Sailor2-20B-Chat-Q2_K.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q2_K.gguf) | Q2_K | 7.393 GB | smallest, significant quality loss - not recommended for most purposes |
| [Sailor2-20B-Chat-Q3_K_S.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q3_K_S.gguf) | Q3_K_S | 8.552 GB | very small, high quality loss |
| [Sailor2-20B-Chat-Q3_K_M.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q3_K_M.gguf) | Q3_K_M | 9.458 GB | very small, high quality loss |
| [Sailor2-20B-Chat-Q3_K_L.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q3_K_L.gguf) | Q3_K_L | 10.239 GB | small, substantial quality loss |
| [Sailor2-20B-Chat-Q4_0.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q4_0.gguf) | Q4_0 | 10.995 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Sailor2-20B-Chat-Q4_K_S.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q4_K_S.gguf) | Q4_K_S | 11.069 GB | small, greater quality loss |
| [Sailor2-20B-Chat-Q4_K_M.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q4_K_M.gguf) | Q4_K_M | 11.622 GB | medium, balanced quality - recommended |
| [Sailor2-20B-Chat-Q5_0.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q5_0.gguf) | Q5_0 | 13.294 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Sailor2-20B-Chat-Q5_K_S.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q5_K_S.gguf) | Q5_K_S | 13.294 GB | large, low quality loss - recommended |
| [Sailor2-20B-Chat-Q5_K_M.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q5_K_M.gguf) | Q5_K_M | 13.618 GB | large, very low quality loss - recommended |
| [Sailor2-20B-Chat-Q6_K.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q6_K.gguf) | Q6_K | 15.737 GB | very large, extremely low quality loss |
| [Sailor2-20B-Chat-Q8_0.gguf](https://huggingface.co/tensorblock/Sailor2-20B-Chat-GGUF/blob/main/Sailor2-20B-Chat-Q8_0.gguf) | Q8_0 | 20.381 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/Sailor2-20B-Chat-GGUF --include "Sailor2-20B-Chat-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/Sailor2-20B-Chat-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```