---
library_name: transformers
pipeline_tag: text-generation
base_model: aisingapore/Llama-SEA-LION-v3-70B-IT
language:
- en
- zh
- vi
- id
- th
- fil
- ta
- ms
- km
- lo
- my
- jv
- su
license: llama3.1
base_model_relation: finetune
tags:
- TensorBlock
- GGUF
---

<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
    <div style="display: flex; flex-direction: column; align-items: flex-start;">
        <p style="margin-top: 0.5em; margin-bottom: 0em;">
            Feedback and support: TensorBlock's  <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
        </p>
    </div>
</div>

## aisingapore/Llama-SEA-LION-v3-70B-IT - GGUF

This repo contains GGUF format model files for [aisingapore/Llama-SEA-LION-v3-70B-IT](https://huggingface.co/aisingapore/Llama-SEA-LION-v3-70B-IT).

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).

## Our projects
<table border="1" cellspacing="0" cellpadding="10">
<tr>
  <th style="font-size: 25px;">Awesome MCP Servers</th>
  <th style="font-size: 25px;">TensorBlock Studio</th>
</tr>
  <tr>
    <th><img src="https://imgur.com/2Xov7B7.jpeg" alt="Project A" width="450"/></th>
    <th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Project B" width="450"/></th>
  </tr>
  <tr>
    <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
    <th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
  </tr>
<tr>
  <th>
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      display: inline-block;
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    ">👀 See what we built 👀</a>
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    ">👀 See what we built 👀</a>
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## Prompt template

```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>

Cutting Knowledge Date: December 2023
Today Date: 26 Jul 2024

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Llama-SEA-LION-v3-70B-IT-Q2_K.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q2_K.gguf) | Q2_K | 26.375 GB | smallest, significant quality loss - not recommended for most purposes |
| [Llama-SEA-LION-v3-70B-IT-Q3_K_S.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q3_K_S.gguf) | Q3_K_S | 30.912 GB | very small, high quality loss |
| [Llama-SEA-LION-v3-70B-IT-Q3_K_M.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q3_K_M.gguf) | Q3_K_M | 34.267 GB | very small, high quality loss |
| [Llama-SEA-LION-v3-70B-IT-Q3_K_L.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q3_K_L.gguf) | Q3_K_L | 37.141 GB | small, substantial quality loss |
| [Llama-SEA-LION-v3-70B-IT-Q4_0.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q4_0.gguf) | Q4_0 | 39.970 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Llama-SEA-LION-v3-70B-IT-Q4_K_S.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q4_K_S.gguf) | Q4_K_S | 40.347 GB | small, greater quality loss |
| [Llama-SEA-LION-v3-70B-IT-Q4_K_M.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q4_K_M.gguf) | Q4_K_M | 42.520 GB | medium, balanced quality - recommended |
| [Llama-SEA-LION-v3-70B-IT-Q5_0.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q5_0.gguf) | Q5_0 | 48.657 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Llama-SEA-LION-v3-70B-IT-Q5_K_S.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q5_K_S.gguf) | Q5_K_S | 48.657 GB | large, low quality loss - recommended |
| [Llama-SEA-LION-v3-70B-IT-Q5_K_M.gguf](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q5_K_M.gguf) | Q5_K_M | 49.950 GB | large, very low quality loss - recommended |
| [Llama-SEA-LION-v3-70B-IT-Q6_K](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q6_K) | Q6_K | 57.888 GB | very large, extremely low quality loss |
| [Llama-SEA-LION-v3-70B-IT-Q8_0](https://huggingface.co/tensorblock/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF/blob/main/Llama-SEA-LION-v3-70B-IT-Q8_0) | Q8_0 | 74.975 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/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF --include "Llama-SEA-LION-v3-70B-IT-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/aisingapore_Llama-SEA-LION-v3-70B-IT-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```