README.md

---
library_name: transformers
datasets:
- IEEEVITPune-AI-Team/chatbotAlpha
language:
- en
---

# Model Card for Model ID
The motivation of this model was to educate the university students about the vast scope that technology has and channeling it via the chatbot we have created. 
This is just a small step that AI Team at IEEE SB VIT Pune has taken to contribute in the vast space of Artificial Intelligence. As our tagline says, "Advancing Technology for Humanity" we believe that AI can truly revolutionize the tech domain forever and hence we have invested in creating a chatbot.

## Model Details


### Model Description

This chatbot is curated by the AI Team(2023-24) at IEEE SB VIT Pune. The primary purpose of this bot is answer questions related to Data Structure and Algorithms, FAQs related to IEEE SB VIT Pune, Research paper based questions, Placement based questions and much more.


- **Developed by:** AI Team (2023-24) [Mrunmayee Phadke (Project Head), Hritesh Maikap, Nidhish W, Arya Lokhande, Apurva Kota, Soham Nimale]
- **Funded by [optional]:** IEEE SB VIT Pune
- **Shared by [optional]:** [More Information Needed]
- **Model type:** Text Generation based model trained on Llama2
- **Language(s):** Python
- **Finetuned from model [optional]:** Llama2

- **Repository:** [Loading...]
- **Paper [optional]:** [Loading...]

## Uses

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### Direct Use

You can directly access the model from the space hosted on our repository. 

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### 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]
- **Compute Region:** [More Information Needed]
- **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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