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typhoon-ai/typhoon-v1.5-72b-instruct-awq
typhoon-v1.5-72b-instruct-awq is a text generation model from typhoon-ai. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
Typhoon-1.5-72B-instruct: Thai Large Language Model (Instruct-AWQ)
Downloads · 30 days
27
5% of all-time downloads
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From the Hugging Face model README
Typhoon-1.5-72B-instruct: Thai Large Language Model (Instruct-AWQ)
Typhoon-1.5-72B-instruct is a instruct Thai 🇹🇭 large language model with 72 billion parameters, and it is based on Qwen1.5-72B.
We also have a newer release of 1.5x 70B, which is better for application use cases. here

For release post, please see our blog.
| Model | ONET | IC | TGAT | TPAT-1 | A-Level | Average (ThaiExam) | M3Exam | MMLU |
|---|---|---|---|---|---|---|---|---|
| Typhoon-1.5 72B | 0.562 | 0.716 | 0.778 | 0.5 | 0.528 | 0.6168 | 0.587 | 0.7271 |
| OpenThaiGPT 1.0.0 70B | 0.447 | 0.492 | 0.778 | 0.5 | 0.319 | 0.5072 | 0.493 | 0.6167 |
| GPT-3.5-turbo(01-2024) | 0.358 | 0.279 | 0.678 | 0.345 | 0.318 | 0.3956 | 0.316 | 0.700** |
| GPT-4(04-2024) | 0.589 | 0.594 | 0.756 | 0.517 | 0.616 | 0.6144 | 0.626 | 0.864** |
from transformers import AutoTokenizer
from vllm import LLM, SamplingParams
quant_path = "scb10x/typhoon-v1.5-72b-instruct-awq"
llm = LLM(model=quant_path, quantization='awq', max_model_len=8192)
tokenizer = AutoTokenizer.from_pretrained(quant_path)
messages = [
{"role": "user", "content": "ขอสูตรไก่ย่าง"},
]
prompts = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=False
)
sampling_params = SamplingParams(repetition_penalty=1.15, top_p=0.6, temperature=0.9, max_tokens=1024, stop=['<|im_end|>', '<|im_start|>'])
outputs = llm.generate(prompts, sampling_params=sampling_params)
print(outputs[0].outputs)
We use chatml chat-template.
{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content']}}{% if (loop.last and add_generation_prompt) or not loop.last %}{{ '<|im_end|>' + '\n'}}{% endif %}{% endfor %}
{% if add_generation_prompt and messages[-1]['role'] != 'assistant' %}{{ '<|im_start|>assistant\n' }}{% endif %}
This model is an instructional model. However, it’s still undergoing development. It incorporates some level of guardrails, but it still may produce answers that are inaccurate, biased, or otherwise objectionable in response to user prompts. We recommend that developers assess these risks in the context of their use case.
https://twitter.com/opentyphoon
@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}
}