Upload folder using huggingface_hub
Browse files- README.md +147 -0
- config.json +27 -0
- generation_config.json +7 -0
- model.safetensors.index.json +330 -0
- output.safetensors +3 -0
- seal_logo.png +0 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +31 -0
README.md
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---
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license: other
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license_name: seallms
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license_link: https://huggingface.co/SeaLLMs/SeaLLM-Chat-13b/blob/main/LICENSE
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extra_gated_prompt: >-
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You agree to not use the models for any harmful, inappropriate, unethical or
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illegal purpose or intention. You agree to perform your own red teaming and
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provide related safety and security measures before deployment for any product
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relevant to our models and demos, and you must abide by and comply with local
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+
governance and regulations. In no event shall the models' authors be held
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liable for any claim, damages, or other liability arising from the use of the
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released weights, codes, or demos. The models and demos may be subject to
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export controls or restrictions in the United States or other countries or
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regions. You shall comply with applicable laws and regulations in your use of
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the demos.
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extra_gated_fields:
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Company: text
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+
Country: text
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language:
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- en
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- vi
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- id
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- ms
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- th
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- km
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- lo
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- my
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- tl
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- zh
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---
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<p align="center">
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<img src="seal_logo.png" width="200" />
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</p>
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# SeaLLMs - Large Language Models for Southeast Asia
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<p align="center">
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<a href="https://huggingface.co/SeaLLMs/SeaLLM-Chat-13b" target="_blank" rel="noopener"> 🤗 Tech Memo</a>
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+
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<a href="https://huggingface.co/spaces/SeaLLMs/SeaLLM-Chat-13b" target="_blank" rel="noopener"> 🤗 DEMO</a>
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<a href="https://github.com/DAMO-NLP-SG/SeaLLMs" target="_blank" rel="noopener">Github</a>
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<a href="https://arxiv.org/pdf/2312.00738.pdf" target="_blank" rel="noopener">Technical Report</a>
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</p>
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## SeaLLM-chat-7B
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This a **7B Chat** version of SeaLLMs. It Vietnamese 🇻🇳, Indonesian 🇮🇩, Thai 🇹🇭, Malay 🇲🇾, Khmer 🇰🇭, Lao 🇱🇦, Tagalog 🇵🇭 and Burmese 🇲🇲.
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It may have lower capability than the 13B models but it is much more memory-efficient and faster.
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Visit our <a href="https://arxiv.org/pdf/2312.00738.pdf" target="_blank" rel="noopener">Technical Report</a> and <a href="https://huggingface.co/SeaLLMs/SeaLLM-Chat-13b" target="_blank" rel="noopener"> 🤗 Tech Memo</a> for more details.
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<blockquote style="color:red">
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<p><strong style="color: red">Terms of Use and License</strong>:
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By using our released weights, codes, and demos, you agree to and comply with the terms and conditions specified in our <a href="https://huggingface.co/SeaLLMs/SeaLLM-Chat-13b/edit/main/LICENSE" target="_blank" rel="noopener">SeaLLMs Terms Of Use</a>.
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</blockquote>
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> **Disclaimer**:
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> We must note that even though the weights, codes, and demos are released in an open manner, similar to other pre-trained language models, and despite our best efforts in red teaming and safety fine-tuning and enforcement, our models come with potential risks, including but not limited to inaccurate, misleading or potentially harmful generation.
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> Developers and stakeholders should perform their own red teaming and provide related security measures before deployment, and they must abide by and comply with local governance and regulations.
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> In no event shall the authors be held liable for any claim, damages, or other liability arising from the use of the released weights, codes, or demos.
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> The logo was generated by DALL-E 3.
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## How to Run:
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SeaLLM models work the same way as Llama-2, so the Llama-2 generation codebase should be sufficient to run.
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However, as this is a chat model, you should wrap the prompt/instruction using the following format function.
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You should also turn off add_special_tokens with `tokenizer.add_special_tokens = False`.
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```python
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BOS_TOKEN = '<s>'
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EOS_TOKEN = '</s>'
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B_INST, E_INST = "[INST]", "[/INST]"
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B_SYS, E_SYS = "<<SYS>>\n", "\n<</SYS>>\n\n"
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SYSTEM_PROMPT = """You are a multilingual, helpful, respectful and honest assistant. \
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Please always answer as helpfully as possible, while being safe. Your \
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answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure \
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that your responses are socially unbiased and positive in nature.
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If a question does not make any sense, or is not factually coherent, explain why instead of answering something not \
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correct. If you don't know the answer to a question, please don't share false information.
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As a multilingual assistant, you must respond and follow instructions in the native language of the user by default, unless told otherwise. \
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Your response should adapt to the norms and customs of the respective language and culture.
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"""
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def chat_multiturn_seq_format(
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message: str,
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history: List[Tuple[str, str]] = None,
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):
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"""
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```
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<bos>[INST] B_SYS SytemPrompt E_SYS Prompt [/INST] Answer <eos>
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<bos>[INST] Prompt [/INST] Answer <eos>
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<bos>[INST] Prompt [/INST]
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```
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As the format auto-add <bos>, please turn off add_special_tokens with `tokenizer.add_special_tokens = False`
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Inputs:
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message: the current prompt
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history: list of list indicating previous conversation. [[message1, response1], [message2, response2]]
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Outputs:
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full_prompt: the prompt that should go into the chat model
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e.g:
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full_prompt = chat_multiturn_seq_format("Hello world")
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output = model.generate(tokenizer.encode(full_prompt, add_special_tokens=False), ...)
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"""
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text = ''
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for i, (prompt, res) in enumerate(history):
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if i == 0:
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text += f"{bos_token}{B_INST} {B_SYS} {sys_prompt} {E_SYS} {prompt} {E_INST}"
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else:
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text += f"{bos_token}{B_INST} {prompt}{end_instr}"
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if res is not None:
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text += f" {res} {eos_token} "
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if len(history) == 0 or text.strip() == '':
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text = f"{bos_token}{B_INST} {B_SYS} {sys_prompt} {E_SYS} {message} {E_INST}"
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else:
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text += f"{bos_token}{B_INST} {message} {E_INST}"
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return text
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```
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## Citation
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If you find our project useful, we hope you would kindly star our repo and cite our work as follows: Corresponding Author: [[email protected]](mailto:[email protected])
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```
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@article{damonlpsg2023seallm,
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author = {Xuan-Phi Nguyen*, Wenxuan Zhang*, Xin Li*, Mahani Aljunied*,
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Qingyu Tan, Liying Cheng, Guanzheng Chen, Yue Deng, Sen Yang,
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Chaoqun Liu, Hang Zhang, Lidong Bing},
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title = {SeaLLMs - Large Language Models for Southeast Asia},
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year = 2023,
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Eprint = {arXiv:2312.00738},
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}
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```
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config.json
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{
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"_name_or_path": "/mnt/workspace/workgroup/phi/hf_train/pretrain_lm/dpo/seallm7b10L7k_a_seaall_sft4x_1_3_dpo_8/step-80000",
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"architectures": [
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"LlamaForCausalLM"
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],
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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"max_position_embeddings": 4096,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 32,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.31.0.dev0",
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"use_cache": true,
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"vocab_size": 48512
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 0,
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"transformers_version": "4.31.0.dev0"
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}
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model.safetensors.index.json
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{
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"metadata": {
|
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"total_size": 13747367936
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},
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