Update README.md

README.md

@@ -1,99 +1,105 @@
----
-license: other
----
-
-## Introduction
-
-Aquila is a large language model independently developed by BAAI. Building upon the Aquila model, we continued pre-training, SFT (Supervised Fine-Tuning), and RL (Reinforcement Learning) through a multi-stage training process, ultimately resulting in the AquilaMed-RL model. This model possesses professional capabilities in the medical field and demonstrates a significant win rate when evaluated against annotated data using the GPT-4 model. The AquilaMed-RL model can perform medical triage, medication inquiries, and general Q&A. We will open-source the SFT data and RL data required for training the model. Additionally, we will release a technical report detailing our methods in developing the model for the medical field, thereby promoting the development of the open-source community.
-
-## Model Details
-
-The training process of the model is described as follows. For more information, please refer to our technical report. https://github.com/FlagAI-Open/industry-application/blob/main/Aquila_med_tech-report.pdf
-
-![pipeline](./img/pipline_2.jpg)
-
-## Evaluation
-
-The subjective and objective scores are as follows。
-
-subjective： Using GPT-4 for evaluation, the win rates of our model compared to the reference answers in the annotated validation dataset are as follows.
-
-Objective：use MMLU / C-EVAL / CMB-exam to evaluate the model
-
-![pipeline](./img/eval-result-med.png)
-
-## usage
-
-Once you have downloaded the model locally, you can use the following code for inference.
-
-```python
-
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig
-
-
-model_dir = "xxx"
-
-tokenizer = AutoTokenizer.from_pretrained(model_dir, trust_remote_code=True)
-
-config = AutoConfig.from_pretrained(model_dir, trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained(
-    model_dir, config=config, trust_remote_code=True
-)
-model.cuda()
-model.eval()
-
-template = "<|im_start|>system\nYou are a helpful assistant in medical domain.<|im_end|>\n<|im_start|>user\n{question}<|im_end|>\n<|im_start|>assistant\n"
-
-text = "我肚子疼怎么办？"
-
-item_instruction = template.format(question=text)
-
-inputs = tokenizer(item_instruction, return_tensors="pt").to("cuda")
-input_ids = inputs["input_ids"]
-prompt_length = len(input_ids[0])
-generate_output = model.generate(
-    input_ids=input_ids, do_sample=False, max_length=1024, return_dict_in_generate=True
-)
-
-response_ids = generate_output.sequences[0][prompt_length:]
-predicts = tokenizer.decode(
-    response_ids, skip_special_tokens=True, clean_up_tokenization_spaces=True
-)
-
-print("predict:", predicts)
-
-
-"""
-predict: 肚子疼可能是多种原因引起的，例如消化不良、胃炎、胃溃疡、胆囊炎、胰腺炎、肠道感染等。如果疼痛持续或加重，或者伴随有呕吐、腹泻、发热等症状，建议尽快就医。如果疼痛轻微，可以尝试以下方法缓解：
-
-1. 饮食调整：避免油腻、辛辣、刺激性食物，多喝水，多吃易消化的食物，如米粥、面条、饼干等。
-
-2. 休息：避免剧烈运动，保持充足的睡眠。
-
-3. 热敷：用热水袋或毛巾敷在肚子上，可以缓解疼痛。
-
-4. 药物：可以尝试一些非处方药，如布洛芬、阿司匹林等，但请务必在医生的指导下使用。
-
-如果疼痛持续或加重，或者伴随有其他症状，建议尽快就医。
-
-希望我的回答对您有所帮助。如果您还有其他问题，欢迎随时向我提问。 
-"""
-```
-
-## License
-
-Aquila series open-source model is licensed under [BAAI Aquila Model Licence Agreement](https://huggingface.co/BAAI/AquilaMed-RL/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf)
-
-
-
-## Citation
-
-If you find our work helpful, feel free to give us a cite.
-
-```
-@article{Aqulia-Med LLM,
-  title={Aqulia-Med LLM: Pioneering Full-Process Open-Source Medical Language Models},
-  year={2024}
-}
+---
+license: other
+---
+
+## Introduction
+
+Aquila is a large language model independently developed by BAAI. Building upon the Aquila model, we continued pre-training, SFT (Supervised Fine-Tuning), and RL (Reinforcement Learning) through a multi-stage training process, ultimately resulting in the AquilaMed-RL model. This model possesses professional capabilities in the medical field and demonstrates a significant win rate when evaluated against annotated data using the GPT-4 model. The AquilaMed-RL model can perform medical triage, medication inquiries, and general Q&A. We will open-source the SFT data and RL data required for training the model. Additionally, we will release a technical report detailing our methods in developing the model for the medical field, thereby promoting the development of the open-source community.
+
+## Model Details
+
+The training process of the model is described as follows. For more information, please refer to our technical report. https://github.com/FlagAI-Open/industry-application/blob/main/Aquila_med_tech-report.pdf
+
+![pipeline](./img/pipline_2.jpg)
+
+
+## Dataset
+we have released our supervised data, you can find the in huggingface
+- SFT: https://huggingface.co/datasets/BAAI/AquilaMed-Instruct
+- RL: https://huggingface.co/datasets/BAAI/AquilaMed-RL
+
+## Evaluation
+
+The subjective and objective scores are as follows。
+
+subjective： Using GPT-4 for evaluation, the win rates of our model compared to the reference answers in the annotated validation dataset are as follows.
+
+Objective：use MMLU / C-EVAL / CMB-exam to evaluate the model
+
+![pipeline](./img/eval-result-med.png)
+
+## usage
+
+Once you have downloaded the model locally, you can use the following code for inference.
+
+```python
+
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig
+
+
+model_dir = "xxx"
+
+tokenizer = AutoTokenizer.from_pretrained(model_dir, trust_remote_code=True)
+
+config = AutoConfig.from_pretrained(model_dir, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_dir, config=config, trust_remote_code=True
+)
+model.cuda()
+model.eval()
+
+template = "<|im_start|>system\nYou are a helpful assistant in medical domain.<|im_end|>\n<|im_start|>user\n{question}<|im_end|>\n<|im_start|>assistant\n"
+
+text = "我肚子疼怎么办？"
+
+item_instruction = template.format(question=text)
+
+inputs = tokenizer(item_instruction, return_tensors="pt").to("cuda")
+input_ids = inputs["input_ids"]
+prompt_length = len(input_ids[0])
+generate_output = model.generate(
+    input_ids=input_ids, do_sample=False, max_length=1024, return_dict_in_generate=True
+)
+
+response_ids = generate_output.sequences[0][prompt_length:]
+predicts = tokenizer.decode(
+    response_ids, skip_special_tokens=True, clean_up_tokenization_spaces=True
+)
+
+print("predict:", predicts)
+
+
+"""
+predict: 肚子疼可能是多种原因引起的，例如消化不良、胃炎、胃溃疡、胆囊炎、胰腺炎、肠道感染等。如果疼痛持续或加重，或者伴随有呕吐、腹泻、发热等症状，建议尽快就医。如果疼痛轻微，可以尝试以下方法缓解：
+
+1. 饮食调整：避免油腻、辛辣、刺激性食物，多喝水，多吃易消化的食物，如米粥、面条、饼干等。
+
+2. 休息：避免剧烈运动，保持充足的睡眠。
+
+3. 热敷：用热水袋或毛巾敷在肚子上，可以缓解疼痛。
+
+4. 药物：可以尝试一些非处方药，如布洛芬、阿司匹林等，但请务必在医生的指导下使用。
+
+如果疼痛持续或加重，或者伴随有其他症状，建议尽快就医。
+
+希望我的回答对您有所帮助。如果您还有其他问题，欢迎随时向我提问。 
+"""
+```
+
+## License
+
+Aquila series open-source model is licensed under [BAAI Aquila Model Licence Agreement](https://huggingface.co/BAAI/AquilaMed-RL/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf)
+
+
+
+## Citation
+
+If you find our work helpful, feel free to give us a cite.
+
+```
+@article{Aqulia-Med LLM,
+  title={Aqulia-Med LLM: Pioneering Full-Process Open-Source Medical Language Models},
+  year={2024}
+}
 ```