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.gitattributes ADDED
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README.md ADDED
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+
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+ ---
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+ # For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
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+ # Doc / guide: https://huggingface.co/docs/hub/model-cards
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+ license: apache-2.0
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+ language:
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+ - zh
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+ widget:
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+ - text: >-
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+ A chat between a curious user and an artificial intelligence assistant.
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+ The assistant gives helpful, detailed, and polite answers to the user's
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+ questions. USER: 你好,請問你可以幫我寫一封推薦信嗎? ASSISTANT:
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ extra_gated_heading: Acknowledge license to accept the repository.
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+ extra_gated_prompt: Please contact the author for access.
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+ extra_gated_button_content: Acknowledge license 同意以上內容
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+ extra_gated_fields:
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+ Name: text
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+ Mail: text
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+ Organization: text
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+ Country: text
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+ Any utilization of the Taiwan LLM repository mandates the explicit acknowledgment and attribution to the original author: checkbox
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+ 使用Taiwan LLM必須明確地承認和歸功於優必達株式會社 Ubitus 以及原始作者: checkbox
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+ ---
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/5df9c78eda6d0311fd3d541f/CmusIT5OlSXvFrbTJ7l-C.png" alt="Taiwan LLM Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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+
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+ # 🌟 Checkout [Taiwan-LLM Demo Chat-UI](http://www.twllm.com) 🌟
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+
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+ # Model Card for Taiwan LLM 7B v2.1 chat
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+
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+ Taiwan LLM is an advanced language model tailored for Traditional Chinese, focusing on the linguistic and cultural contexts of Taiwan.
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+ Developed from a large base model, it's enriched with diverse Taiwanese textual sources and refined through Supervised Fine-Tuning.
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+ This model excels in language understanding and generation, aligning closely with Taiwan's cultural nuances.
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+ It demonstrates improved performance on various benchmarks like TC-Eval, showcasing its contextual comprehension and cultural relevance.
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+ For detailed insights into Taiwan LLM's development and features, refer to our [technical report](https://github.com/MiuLab/Taiwan-LLaMa/blob/main/twllm_paper.pdf).
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+
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+
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+ ## Model description
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+
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+ - **Model type:** A 7B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
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+ - **Language(s) (NLP):** Primarily Traditional Chinese (zh-tw)
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+ - **Finetuned from model:** [yentinglin/Taiwan-LLM-7B-v2.0-base](https://huggingface.co/yentinglin/yentinglin/Taiwan-LLM-7B-v2.0-base)
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+
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+ ### Model Sources
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+
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+ <!-- Provide the basic links for the model. -->
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+
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+ - **Repository:** https://github.com/MiuLab/Taiwan-LLaMa
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+ - **Demo:** https://twllm.com/
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+
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+ ## Performance
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+
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5df9c78eda6d0311fd3d541f/HTwIzw6RDha2-PhuWqSuI.png)
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+
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+ ## Intended uses
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+
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+ Here's how you can run the model using the `pipeline()` function from 🤗 Transformers:
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+
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+ ```python
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+ # pip install transformers>=4.34
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+ # pip install accelerate
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+
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+ import torch
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+ from transformers import pipeline
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+
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+ pipe = pipeline("text-generation", model="yentinglin/Taiwan-LLM-7B-v2.1-chat", torch_dtype=torch.bfloat16, device_map="auto")
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+
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+ # We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
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+ messages = [
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+ {
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+ "role": "system",
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+ "content": "你是一個人工智慧助理",
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+ },
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+ {"role": "user", "content": "東北季風如何影響台灣氣候?"},
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+ ]
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+ prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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+ outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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+ print(outputs[0]["generated_text"])
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+ ```
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+
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+ ### Training hyperparameters
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5df9c78eda6d0311fd3d541f/MdvHwdUvH-c926qyRAw7K.png)
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5df9c78eda6d0311fd3d541f/kKpkvxDzOEyiAoTqmzRYO.png)
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+
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5df9c78eda6d0311fd3d541f/FsnlJ_fkRxf7fn5RKZnjE.png)
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - distributed_type: multi-GPU
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.03
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+ - num_epochs: 5.0
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+
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+ ## Citation
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+
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+ If you find Taiwan LLM is useful in your work, please cite it with:
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+
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+ ```
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+ @misc{lin2023taiwan,
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+ title={Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model},
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+ author={Yen-Ting Lin and Yun-Nung Chen},
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+ year={2023},
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+ eprint={2311.17487},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL}
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+ }
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+ ```
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+
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+ # Acknowledgement
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+
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+ Taiwan LLM v2 is conducted in collaboration with [Ubitus K.K.](http://ubitus.net). Ubitus provides valuable compute resources for the project.
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+ "normalized": false,
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+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ }
29
+ },
30
+ "bos_token": "<s>",
31
+ "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'].strip() %}{% else %}{% set loop_messages = messages %}{% set system_message = '你是人工智慧助理,以下是用戶和人工智能助理之間的對話。你要對用戶的問題提供有用、安全、詳細和禮貌的回答。' %}{% endif %}{{system_message + eos_token}}{% for message in loop_messages %}{% if message['role'] == 'user' %}USER: {{ message['content'].strip() + eos_token }}{% elif message['role'] == 'system' %}{{message['content'].strip() + eos_token}}{% elif message['role'] == 'assistant' %}ASSISTANT: {{ message['content'].strip() + eos_token }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{'ASSISTANT:'}}{% endif %}",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "legacy": false,
35
+ "model_max_length": 4096,
36
+ "pad_token": "<unk>",
37
+ "padding_side": "right",
38
+ "sp_model_kwargs": {},
39
+ "spaces_between_special_tokens": false,
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": true
43
+ }