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Model: klyang/MentaLLaMA-chat-13B Source: Original Platform
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README.md
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---
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license: mit
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language:
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- en
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metrics:
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- f1
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tags:
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- medical
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---
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# Introduction
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MentaLLaMA-chat-13B is part of the [MentaLLaMA](https://github.com/SteveKGYang/MentalLLaMA) project, the first open-source large language model (LLM) series for
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interpretable mental health analysis with instruction-following capability. This model is finetuned based on the Meta LLaMA2-chat-13B foundation model and the full IMHI instruction tuning data.
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The model is expected to make complex mental health analyses for various mental health conditions and give reliable explanations for each of its predictions.
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It is fine-tuned on the IMHI dataset with 75K high-quality natural language instructions to boost its performance in downstream tasks.
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We perform a comprehensive evaluation on the IMHI benchmark with 20K test samples. The result shows that MentalLLaMA approaches state-of-the-art discriminative
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methods in correctness and generates high-quality explanations.
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# Ethical Consideration
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Although experiments on MentaLLaMA show promising performance on interpretable mental health analysis, we stress that
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all predicted results and generated explanations should only used
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for non-clinical research, and the help-seeker should get assistance
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from professional psychiatrists or clinical practitioners. In addition,
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recent studies have indicated LLMs may introduce some potential
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bias, such as gender gaps. Meanwhile, some incorrect prediction results, inappropriate explanations, and over-generalization
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also illustrate the potential risks of current LLMs. Therefore, there
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are still many challenges in applying the model to real-scenario
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mental health monitoring systems.
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## Other Models in MentaLLaMA
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In addition to MentaLLaMA-chat-13B, the MentaLLaMA project includes another model: MentaLLaMA-chat-7B, MentalBART, MentalT5.
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- **MentaLLaMA-chat-7B**: This model is finetuned based on the Meta LLaMA2-chat-7B foundation model and the full IMHI instruction tuning data. The training data covers
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10 mental health analysis tasks.
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- **MentalBART**: This model is finetuned based on the BART-large foundation model and the full IMHI-completion data. The training data covers
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10 mental health analysis tasks. This model doesn't have instruction-following ability but is more lightweight and performs well in interpretable mental health analysis
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in a completion-based manner.
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- **MentalT5**: This model is finetuned based on the T5-large foundation model and the full IMHI-completion data. The training data covers
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10 mental health analysis tasks. This model doesn't have instruction-following ability but is more lightweight and performs well in interpretable mental health analysis
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in a completion-based manner.
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## Usage
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You can use the MentaLLaMA-chat-13B model in your Python project with the Hugging Face Transformers library. Here is a simple example of how to load the model:
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```python
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from transformers import LlamaTokenizer, LlamaForCausalLM
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tokenizer = LlamaTokenizer.from_pretrained('klyang/MentaLLaMA-chat-13B')
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model = LlamaForCausalLM.from_pretrained('klyang/MentaLLaMA-chat-13B', device_map='auto')
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```
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In this example, LlamaTokenizer is used to load the tokenizer, and LlamaForCausalLM is used to load the model. The `device_map='auto'` argument is used to automatically
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use the GPU if it's available.
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## License
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MentaLLaMA-chat-13B is licensed under MIT. For more details, please see the MIT file.
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## Citation
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If you use MentaLLaMA-chat-7B in your work, please cite our paper:
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```bibtex
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@misc{yang2023mentalllama,
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title={MentalLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models},
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author={Kailai Yang and Tianlin Zhang and Ziyan Kuang and Qianqian Xie and Sophia Ananiadou},
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year={2023},
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eprint={2309.13567},
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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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||||
24
special_tokens_map.json
Normal file
24
special_tokens_map.json
Normal file
@@ -0,0 +1,24 @@
|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
93391
tokenizer.json
Normal file
93391
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
37
tokenizer_config.json
Normal file
37
tokenizer_config.json
Normal file
@@ -0,0 +1,37 @@
|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
},
|
||||
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|
||||
}
|
||||
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
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|
||||
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|
||||
size 4027
|
||||
Reference in New Issue
Block a user