File size: 3,714 Bytes
84b5790 d154021 f958567 d154021 8d9dcdc 90575a4 8170ac1 c807623 4b280f3 d76adf9 df1e2df 4b280f3 29c024d 9387e34 d154021 da8eb6f 1d907df ca73e60 349ba54 2739473 f7399ae af1efab dc211bc 9d2cdda 4264b85 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
---
license: apache-2.0
language:
- zh
library_name: transformers
pipeline_tag: text-generation
tags:
- Doctor_consultation
- Taiwan
- fine-tuning
- medicine
---
# 🔎 Taiwan-inquiry_7B_v_2.1
<!-- Provide a quick summary of what the model is/does. -->
"The model was fine-tuned based on the **Breeze-7B-Instruct-v1_0** model using a dataset that includes 614 authentic dialogues from the National Cheng Kung University Hospital.
Additionally, 336 synthetic dialogues were included in the training set, carefully crafted to encompass themes drawn from sample questions of the OSCE (臨床技能測驗) sample questions in Taiwan.
These synthetic dialogues were generated using GPT-3.5, Gemini-Pro and Breexe-8x7B-Instruct-v0_1.
The training process was geared towards simulating verbal exchanges between doctors and patients within a hospital environment."
<img src="https://cdn-uploads.huggingface.co/production/uploads/65c07d1b2357c1bded7a92fa/e7QbiYh07kcGwyKniAo0e.png" alt="image/png" style="width:80%; height:auto;">
**************************** **Updates** ****************************
* 2024/04/25 🎉 Released [Taiwan-inquiry_7B_v2.1-awq](https://huggingface.co/ChenWeiLi/Taiwan-inquiry_7B_v2.1-awq)
* 2024/04/29 🎉 Released [Taiwan-inquiry_7B_v2.1.gguf](https://huggingface.co/ChenWeiLi/Taiwan-inquiry_7B_v2.1.gguf)
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [Joseph (Chen-Wei) Li](https://www.linkedin.com/in/joseph-li-3a453b231/), researcher assistant from National Taiwan University Hospital.
- **Model type:** A 7B parameter GPT-like model fine-tuned on a combination of private and synthetic dialogue datasets.
- **Language(s) (NLP):** Traditional Chinese (zh-tw)
- **Finetuned from model :** [Breeze-7B-Instruct-v1_0 ](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v1_0)
### Usage of the model
- The user can take on the role of a doctor, and the model can engage in conversation with you as if it were a patient.
- You can provide the model with a brief patient background in the system prompt, and the model will respond based on that prompt. **(using my patient generator: [**colab**](https://colab.research.google.com/drive/17MSob_tQ2hPtMBL0xOF2zzV6WWe4dEG6?usp=sharing))**
- Directly asking the certain disease about the symptoms and the possible therapies.**（Warning: It's not medical advice!)**
### Model evaluation
The model got the **TMMLU+** (0 shot) performance using [EleutherAI/lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) with default settings.
|Details on TMMLU+ (0 shot):<br/>Model | Base Model | STEM | Social Science | Humanities | Other | AVG |
|-----------------------------------------------------|:---------------------:|:---------------:|:--------------:|:----------:|:----------:|:-------:|
| Taiwan-inquiry_7B_v2.1 |Breeze-7B-Instruct-v1_0| 36.06 | 44.61 | 37.49 | 39.61 | 40.29 |
| Taiwan-inquiry_7B_v2.0 |Breeze-7B-Instruct-v0_1| 36.17 | 43.59 | 35.45 | 37.63 | 38.95 |
| Taiwan-inquiry_7B_v1.0 |Taiwan-LLM-7B-v2.1-chat| 26.74 | 29.47 | 26.83 | 29.61 | 28.83 |
### DEMO
- **User: <span style="color: orange;">doctor</span>**
- **Chatbot: <span style="color: gray;">patient</span>**
|