Instructions to use chanios/typhoon-7B-4.0bpw-exl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use chanios/typhoon-7B-4.0bpw-exl2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="chanios/typhoon-7B-4.0bpw-exl2")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("chanios/typhoon-7B-4.0bpw-exl2")
model = AutoModelForCausalLM.from_pretrained("chanios/typhoon-7B-4.0bpw-exl2")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use chanios/typhoon-7B-4.0bpw-exl2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "chanios/typhoon-7B-4.0bpw-exl2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chanios/typhoon-7B-4.0bpw-exl2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/chanios/typhoon-7B-4.0bpw-exl2

SGLang

How to use chanios/typhoon-7B-4.0bpw-exl2 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "chanios/typhoon-7B-4.0bpw-exl2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chanios/typhoon-7B-4.0bpw-exl2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "chanios/typhoon-7B-4.0bpw-exl2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chanios/typhoon-7B-4.0bpw-exl2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use chanios/typhoon-7B-4.0bpw-exl2 with Docker Model Runner:
```
docker model run hf.co/chanios/typhoon-7B-4.0bpw-exl2
```

Typhoon-7B: Thai Large Language Model

Typhoon-7B is a pretrained Thai 🇹🇭 large language model with 7 billion parameters, and it is based on Mistral-7B.

Typhoon-7B outperforms all open-source Thai language models at the time of writing as evaluated on Thai examination benchmarks, and its instruction-tuned variant achieves the best results in instruction-following tasks. Also, its performance in Thai is on par with GPT-3.5 while being 2.62 times more efficient in tokenizing Thai text.

For full details of this model, please read our paper.

Model Description

Model type: A 7B pretrained decoder-only model
Requirement: transformers 4.34.0 or newer.
Primary Language(s): Thai 🇹🇭 and English 🇬🇧
License: Apache-2.0 (Commercial)

Performance on Thai Benchmark

Model	ONET	IC	TGAT	TPAT-1	A-Level
Typhoon-7B	0.379	0.393	0.700	0.414	0.324
SeaLLM-7B	0.342	0.256	0.589	0.336	0.305
OpenThaiGPT-beta-7B	0.180	0.278	0.411	0.319	0.243
WangChanGLM	0.192	0.271	0.167	0.172	0.175
SEA-LION-7B	0.179	0.290	0.244	0.198	0.175
Avg. Human	0.318	-	0.472	0.406	-

Intended Uses & Limitations

This model is a pretrained base model. Thus, it may not be able to follow human instructions without using one/few-shot learning or instruction fine-tuning. The model does not have any moderation mechanisms, and may generate harmful or inappropriate responses.

SCB10X AI Team

Kunat Pipatanakul, Phatrasek Jirabovonvisut, Potsawee Manakul, Sittipong Sripaisarnmongkol, Ruangsak Patomwong, Pathomporn Chokchainant, Kasima Tharnpipitchai
If you find Typhoon-7B useful for your work, please cite it using:

@article{pipatanakul2023typhoon,
    title={Typhoon: Thai Large Language Models}, 
    author={Kunat Pipatanakul and Phatrasek Jirabovonvisut and Potsawee Manakul and Sittipong Sripaisarnmongkol and Ruangsak Patomwong and Pathomporn Chokchainant and Kasima Tharnpipitchai},
    year={2023},
    journal={arXiv preprint arXiv:2312.13951},
    url={https://arxiv.org/abs/2312.13951}
}

Contact Us

E-mail: kasima@scb10x.com

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Paper for chanios/typhoon-7B-4.0bpw-exl2

Typhoon: Thai Large Language Models

Paper • 2312.13951 • Published Dec 21, 2023 • 7