Update README.md

README.md

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 - AceGPT-7B-Chat
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 # InfectA-Chat
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 <!--To prevent adversial effects of infectious diseases, clear and accessible communication, tracking infectious diseases regularly is crucial. InfectA-Chat is a generative model specifically designed to address this need. Built upon the powerful AceGPT-7B-Chat pre-trained model, InfectA-Chat is fine-tuned to track infectious diseases outbreaks in the infectious diseases domain. This makes it a valuable tool for facilitating communication in both Arabic and English, potentially bridging language barriers and fostering a deeper understanding of infectious diseases.-->
 
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
-
-## Model Details
+# Model Details
 <!--In the fight against infectious diseases in the Middle East, clear and effective communication is paramount. We're excited to announce the release of InfectA-Chat, a generative text model fine-tuned on the AceGPT-7B-Chat model. Designed specifically for the Arabic and English languages, InfectA-Chat excels at following instructions related to infectious disease topics. Notably, our models outperform existing Arabic and state-of-the-art LLMs on Q&A task involving infectious disease instructions while competing with GPT-4. This advancement has the potential to significantly improve communication and disease tracking efforts in the specific region.-->
-### Model Description
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-<!-- Provide a longer summary of what this model is. -->
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-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
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-### Model Sources [optional]
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-<!-- Provide the basic links for the model. -->
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-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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-### Direct Use
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-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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-[More Information Needed]
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-### Downstream Use [optional]
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-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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-[More Information Needed]
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-### Out-of-Scope Use
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-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-[More Information Needed]
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-## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+- **Developed by:** [Korea Institute of Science and Technology]
+- **Language(s) (NLP):** [Arabic, English]
+- **License:** [Creative Commons Attribution 2.0]
+- **Finetuned from model [optional]:** [AceGPT-7B-Chat]
+- **Repository:** [KISTI-AI/InfectA-Chat]
 
-[More Information Needed]
+# Training Details
 
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
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-[More Information Needed]
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-## Training Details
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-### Training Data
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-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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-[More Information Needed]
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-### Training Procedure
+## Training Data
+<!-- InfectA-Chat was instruction fine-tuned with 55,400 infectious diseases-related instruction-following data.-->
 
+## Training Procedure
 <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
 
-#### Preprocessing [optional]
+## Training Hyperparameters
 
-[More Information Needed]
+- **Training regime:** [fp32] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
 
+# Evaluation
 
-#### Training Hyperparameters
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-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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-#### Speeds, Sizes, Times [optional]
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-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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-[More Information Needed]
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-## Evaluation
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+## Evaluation Results on Infectious Diseases-related Instruction-Following Dataset
 <!-- Experiments on infectious diseases-related instruction-following data and Arabic MMLU benchmark dataset. ‘STEM’, ‘Humanities’, ‘Social Sciences’, ‘Others’ belong to Arabic MMLU.  -->
 
-
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6516795fb84fb7bc6cc34fd9/CQnUnZUWNqlJIM2F77mde.png)
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6516795fb84fb7bc6cc34fd9/xpVldjeKc3zWIWAMAjPlS.png)
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6516795fb84fb7bc6cc34fd9/r32DDr7iqG-6WY21bwfPO.png)
 
-### Testing Data, Factors & Metrics
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-#### Testing Data
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-<!-- This should link to a Dataset Card if possible. -->
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-[More Information Needed]
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-#### Factors
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-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-[More Information Needed]
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-#### Metrics
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-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-[More Information Needed]
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-### Results
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-[More Information Needed]
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-#### Summary
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-## Model Examination [optional]
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-<!-- Relevant interpretability work for the model goes here -->
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-[More Information Needed]
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-## Environmental Impact
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-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
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-## Technical Specifications [optional]
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-### Model Architecture and Objective
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-[More Information Needed]
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-### Compute Infrastructure
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-[More Information Needed]
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-#### Hardware
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-[More Information Needed]
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-#### Software
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-[More Information Needed]
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-## Citation [optional]
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-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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-**BibTeX:**
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-[More Information Needed]
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-**APA:**
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-[More Information Needed]
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-## Glossary [optional]
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-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-[More Information Needed]
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-## More Information [optional]
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-[More Information Needed]
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-## Model Card Authors [optional]
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-[More Information Needed]
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-## Model Card Contact
+## Evaluation Results on Arabic MMLU Benchmark Dataset
 
-[More Information Needed]
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6516795fb84fb7bc6cc34fd9/duwgP2pRuPGqd5o-wCNuy.png)