transformers safetensors gpt2 text-generation conversational arxiv:1910.09700 autotrain_compatible text-generation-inference endpoints_compatible region:us
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library_name: transformers
tags: []
---

# Model Card for Model ID
Anjanams04/healthbot

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## Model Details

### Model Description
This is a fine-tuned version of DialoGPT on medical data aimed at creating a health assistant chatbot. The model is intended to engage in medical-related conversations, offering insights based on input symptoms and questions.
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** Anjana MS
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** Anjana MS
- **Model type:** Conversational AI (based on DialoGPT-medium)
- **Language(s) (NLP):** English
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** microsoft/DialoGPT-medium

### Model Sources [optional]

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- **Repository:** Anjanams04/healthbot
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

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### Direct Use
This model can be used for developing a medical chatbot or virtual health assistant that interacts with users about symptoms, general health advice, and information about diseases.

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### Downstream Use [optional]

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Healthcare providers for chatbot-based pre-diagnosis assistance.
Integration into healthcare apps for automated medical inquiry handling.

### Out-of-Scope Use

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This model should not be used for making clinical decisions or giving final medical advice, as it lacks real-world medical certifications.



## Bias, Risks, and Limitations

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This model has potential biases, as it was trained on limited medical data. It may not represent the full spectrum of medical advice or perspectives. Additionally, incorrect diagnoses or recommendations could result from the conversational nature of the model.

### Recommendations

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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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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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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).

- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]

## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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#### Hardware

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#### Software

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## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Model Card Authors [optional]

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## Model Card Contact

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