--- language: - en - th license: llama3 tags: - instruct - chat pipeline_tag: text-generation model-index: - name: llama-3-typhoon-v1.5-8b-instruct results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 60.41 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=scb10x/llama-3-typhoon-v1.5-8b-instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 80.79 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=scb10x/llama-3-typhoon-v1.5-8b-instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 64.46 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=scb10x/llama-3-typhoon-v1.5-8b-instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 53.25 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=scb10x/llama-3-typhoon-v1.5-8b-instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 77.66 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=scb10x/llama-3-typhoon-v1.5-8b-instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 57.16 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=scb10x/llama-3-typhoon-v1.5-8b-instruct name: Open LLM Leaderboard --- **Llama-3-Typhoon-v1.5-8B: Thai Large Language Model (Instruct)** **Llama-3-Typhoon-v1.5-8B-instruct** is a *instruct* Thai 🇹🇭 large language model with 8 billion parameters, and it is based on Llama3-8B. ![Typhoon 1.5 8b benchmark](https://storage.googleapis.com/typhoon-public/assets/1.5-8b-benchmark.png) For release post, please see our [blog](https://blog.opentyphoon.ai/typhoon-1-5-release-a9364cb8e8d7). *To acknowledge Meta's effort in creating the foundation model and to comply with the license, we explicitly include "llama-3" in the model name. ## **Model Description** - **Model type**: A 8B instruct decoder-only model based on Llama architecture. - **Requirement**: transformers 4.38.0 or newer. - **Primary Language(s)**: Thai 🇹🇭 and English 🇬🇧 - **License**: [Llama 3 Community License](https://llama.meta.com/llama3/license/) ## **Performance** | Model | ONET | IC | TGAT | TPAT-1 | A-Level | Average (ThaiExam) | M3Exam | MMLU | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Typhoon-1.0 (Mistral) | 0.379 | 0.393 | 0.700 | 0.414 | 0.324 | 0.442 | 0.391 | 0.547 | | Typhoon-1.5 8B (Llama3) | ***0.446*** | ***0.431*** | ***0.722*** | ***0.526*** | ***0.407*** | ***0.506*** | ***0.460*** | ***0.614*** | | Sailor 7B | 0.372 | 0.379 | 0.678 | 0.405 | 0.396 | 0.446 | 0.411 | 0.553 | | SeaLLM 2.0 7B | 0.327 | 0.311 | 0.656 | 0.414 | 0.321 | 0.406 | 0.354 | 0.579 | | OpenThaiGPT 1.0.0 7B | 0.238 | 0.249 | 0.444 | 0.319 | 0.289 | 0.308 | 0.268 | 0.369 | | SambaLingo-Thai-Chat 7B | 0.251 | 0.241 | 0.522 | 0.302 | 0.262 | 0.316 | 0.309 | 0.388 | ## Usage Example ```python from transformers import AutoTokenizer, AutoModelForCausalLM import torch model_id = "scb10x/llama-3-typhoon-v1.5-8b-instruct" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype=torch.bfloat16, device_map="auto", ) messages = [ {"role": "system", "content": "You are a helpful assistant who're always speak Thai."}, {"role": "user", "content": "ขอสูตรไก่ย่าง"}, ] input_ids = tokenizer.apply_chat_template( messages, add_generation_prompt=True, return_tensors="pt" ).to(model.device) terminators = [ tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids("<|eot_id|>") ] outputs = model.generate( input_ids, max_new_tokens=512, eos_token_id=terminators, do_sample=True, temperature=0.4, top_p=0.9, ) response = outputs[0][input_ids.shape[-1]:] print(tokenizer.decode(response, skip_special_tokens=True)) ``` ## Chat Template We use llama3 chat-template. ```python {% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %} ``` ## **Intended Uses & Limitations** 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. ## **Follow us** **https://twitter.com/opentyphoon** ## **Support** **https://discord.gg/CqyBscMFpg** ## **SCB10X AI Team** - Kunat Pipatanakul, Potsawee Manakul, Sittipong Sripaisarnmongkol, Pathomporn Chokchainant, Kasima Tharnpipitchai - If you find Typhoon-8B 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](mailto:kasima@scb10x.com)**, **[pathomporn@scb10x.com](mailto:pathomporn@scb10x.com)** - Technical: **[kunat@scb10x.com](mailto:kunat@scb10x.com)** # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_scb10x__llama-3-typhoon-v1.5-8b-instruct) | Metric |Value| |---------------------------------|----:| |Avg. |65.62| |AI2 Reasoning Challenge (25-Shot)|60.41| |HellaSwag (10-Shot) |80.79| |MMLU (5-Shot) |64.46| |TruthfulQA (0-shot) |53.25| |Winogrande (5-shot) |77.66| |GSM8k (5-shot) |57.16|