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Model: WaltonFuture/Diabetica-7B Source: Original Platform
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README.md
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---
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library_name: transformers
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pipeline_tag: text-generation
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license: mit
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base_model:
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- Qwen/Qwen2-7B-Instruct
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tags:
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- medical
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datasets:
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- WaltonFuture/Diabetica-SFT
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---
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# Diabetica-7B
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<div align="center">
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<h2>
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Diabetica: Adapting Large Language Model to Enhance Multiple Medical Tasks in Diabetes Care and Management
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</h2>
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</div>
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<p align="center">
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<a href="https://github.com/waltonfuture/Diabetica" target="_blank">Code</a>｜<a href="https://arxiv.org/pdf/2409.13191" target="_blank">Paper</a> | <a href="https://huggingface.co/datasets/WaltonFuture/Diabetica-SFT" target="_blank">Dataset</a><br>
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</p>
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## Introduction
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Hello! Welcome to the huggingface repository for [Diabetica](https://arxiv.org/pdf/2409.13191).
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Our study introduced a reproducible framework for developing a specialized LLM capable of handling various diabetes tasks. We present three key contributions:
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- High-performance domain-specific model: Compared with previous generic LLMs, our model Diabetica, showed superior performance across a broad range of diabetes-related tasks, including diagnosis, treatment recommendations, medication management, lifestyle advice, patient education, and so on.
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- Reproducible framework: We offered a detailed method for creating specialized medical LLMs using open-source models, curated disease-specific datasets, and fine-tuning techniques. This approach can be adapted to other medical fields, potentially accelerating AI-assisted care development.
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- Comprehensive evaluation: We designed comprehensive benchmarks and conducted clinical trials to validate the model's effectiveness in clinical applications. This ensured our model's practical utility and sets a new standard for evaluating AI tools in diabetes care.
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Please refer to our [GitHub Repo](https://github.com/waltonfuture/Diabetica) for more details.
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## Model Inference
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```bash
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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device = "cuda" # the device to load the model onto
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model_path = 'WaltonFuture/Diabetica-7B'
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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torch_dtype="auto",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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def model_output(content):
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": content}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(device)
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generated_ids = model.generate(
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model_inputs.input_ids,
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max_new_tokens=2048,
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do_sample=True,
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)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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return response
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prompt = "Hello! Please tell me something about diabetes."
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response = model_output(prompt)
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print(response)
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```
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## Citation
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```
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@article{wei2024adapted,
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title={An adapted large language model facilitates multiple medical tasks in diabetes care},
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author={Wei, Lai and Ying, Zhen and He, Muyang and Chen, Yutong and Yang, Qian and Hong, Yanzhe and Lu, Jiaping and Li, Xiaoying and Huang, Weiran and Chen, Ying},
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journal={arXiv preprint arXiv:2409.13191},
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year={2024}
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}
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```
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config.json
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|
||||
"model.norm.weight": "model-00003-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
14
special_tokens_map.json
Normal file
14
special_tokens_map.json
Normal file
@@ -0,0 +1,14 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>"
|
||||
],
|
||||
"eos_token": "<|im_end|>",
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
303112
tokenizer.json
Normal file
303112
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
43
tokenizer_config.json
Normal file
43
tokenizer_config.json
Normal file
@@ -0,0 +1,43 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user