Text Generation
Transformers
Safetensors
Thai
English
qwen2
conversational
text-generation-inference
Instructions to use typhoon-ai/typhoon-v1.5-72b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use typhoon-ai/typhoon-v1.5-72b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="typhoon-ai/typhoon-v1.5-72b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("typhoon-ai/typhoon-v1.5-72b") model = AutoModelForMultimodalLM.from_pretrained("typhoon-ai/typhoon-v1.5-72b") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use typhoon-ai/typhoon-v1.5-72b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "typhoon-ai/typhoon-v1.5-72b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "typhoon-ai/typhoon-v1.5-72b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/typhoon-ai/typhoon-v1.5-72b
- SGLang
How to use typhoon-ai/typhoon-v1.5-72b 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 "typhoon-ai/typhoon-v1.5-72b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "typhoon-ai/typhoon-v1.5-72b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "typhoon-ai/typhoon-v1.5-72b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "typhoon-ai/typhoon-v1.5-72b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use typhoon-ai/typhoon-v1.5-72b with Docker Model Runner:
docker model run hf.co/typhoon-ai/typhoon-v1.5-72b
Typhoon-1.5-72B: Thai Large Language Model (Pretrained)
Typhoon-1.5-72B is a pretrained Thai 🇹🇠large language model with 72 billion parameters, and it is based on Qwen1.5-72B.
For release post, please see our blog.
Model Description
- Model type: A 72B instruct decoder-only model based on Qwen1.5 archtecture.
- Requirement: transformers 4.38.0 or newer.
- Primary Language(s): Thai 🇹🇠and English 🇬🇧
- License: Qwen License
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.
Follow us
https://twitter.com/opentyphoon
Support / Ask any question
SCB10X AI Team
- Kunat Pipatanakul, Potsawee Manakul, Sittipong Sripaisarnmongkol, Natapong Nitarach, Pathomporn Chokchainant, Kasima Tharnpipitchai
- If you find Typhoon-72B 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
- General & Collaboration: kasima@scb10x.com, pathomporn@scb10x.com
- Technical: kunat@scb10x.com
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