Instructions to use SeaLLMs/SeaLLM-7B-v2.5-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SeaLLMs/SeaLLM-7B-v2.5-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="SeaLLMs/SeaLLM-7B-v2.5-GGUF",
	filename="seallm-7b-v2.5-chatml.Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use SeaLLMs/SeaLLM-7B-v2.5-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M

Use Docker

docker model run hf.co/SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use SeaLLMs/SeaLLM-7B-v2.5-GGUF with Ollama:
```
ollama run hf.co/SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M
```

Unsloth Studio

How to use SeaLLMs/SeaLLM-7B-v2.5-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for SeaLLMs/SeaLLM-7B-v2.5-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for SeaLLMs/SeaLLM-7B-v2.5-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SeaLLMs/SeaLLM-7B-v2.5-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use SeaLLMs/SeaLLM-7B-v2.5-GGUF with Docker Model Runner:
```
docker model run hf.co/SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M
```

Lemonade

How to use SeaLLMs/SeaLLM-7B-v2.5-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SeaLLMs/SeaLLM-7B-v2.5-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.SeaLLM-7B-v2.5-GGUF-Q4_K_M

List all available models

lemonade list

SeaLLM-7B-v2.5 - Large Language Models for Southeast Asia

LM-studio/llama.cpp users must set --repeat-penalty to 1 instead of default 1.1

Technical Blog 🤗 Tech Memo 🤗 DEMO Github Technical Report

seallm-7b-v2.5-chatml.Q4_K_M.gguf use ChatML format by changing <eos> to <|im_end|>
seallm-7b-v2.5.Q4_K_M.gguf use SeaLLM-7B-v2.5 format, must download seallm-v2.5.preset.json for LM-studio.

We introduce SeaLLM-7B-v2.5, the state-of-the-art multilingual LLM for Southeast Asian (SEA) languages 🇬🇧 🇨🇳 🇻🇳 🇮🇩 🇹🇭 🇲🇾 🇰🇭 🇱🇦 🇲🇲 🇵🇭. It is the most significant upgrade since SeaLLM-13B, with half the size, outperforming performance across diverse multilingual tasks, from world knowledge, math reasoning, instruction following, etc.

Checkout SeaLLM-7B-v2.5 page for more details.

Citation

If you find our project useful, we hope you would kindly star our repo and cite our work as follows: Corresponding Author: l.bing@alibaba-inc.com

Author list and order will change!

* and ^ are equal contributions.

@article{damonlpsg2023seallm,
  author = {Xuan-Phi Nguyen*, Wenxuan Zhang*, Xin Li*, Mahani Aljunied*, Weiwen Xu, Hou Pong Chan,
            Zhiqiang Hu, Chenhui Shen^, Yew Ken Chia^, Xingxuan Li, Jianyu Wang,
            Qingyu Tan, Liying Cheng, Guanzheng Chen, Yue Deng, Sen Yang,
            Chaoqun Liu, Hang Zhang, Lidong Bing},
  title = {SeaLLMs - Large Language Models for Southeast Asia},
  year = 2023,
  Eprint = {arXiv:2312.00738},
}

Downloads last month: 173

GGUF

Model size

9B params

Architecture

gemma

Hardware compatibility

4-bit

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Collection including SeaLLMs/SeaLLM-7B-v2.5-GGUF

SeaLLM-7B-v2.5

Collection

SeaLLM-7B-v2.5 and its quantized variants. • 3 items • Updated Jul 11, 2024

Paper for SeaLLMs/SeaLLM-7B-v2.5-GGUF

SeaLLMs -- Large Language Models for Southeast Asia

Paper • 2312.00738 • Published Dec 1, 2023 • 25