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| language: en |
| tags: |
| - chatbot |
| - natural language processing |
| license: Apache 2.0 |
| datasets: |
| - Custom Dataset (Dronealexa) |
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| Model Card: NLP-Based Chatbot |
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| Overview |
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| The NLP-Based Chatbot is designed to explore Science & Technology topics. It utilizes a combination of semantic search and summarization techniques to provide relevant and concise responses to user queries. |
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| Model Details |
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| - **Model Name:** NLP-Based Chatbot |
| - **Model Type:** Natural Language Processing (NLP) Chatbot |
| - **Framework:** Gradio Blocks Interface, spaCy, Transformers |
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| Components |
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| 1. Semantic Search |
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| The chatbot employs semantic search to retrieve relevant information from a preprocessed dataset (Dronealexa.csv). The search is based on a TF-IDF vectorizer and cosine similarity calculations. |
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| 2. Summarization |
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| A summarization pipeline is used to generate concise summaries of the retrieved information. The Hugging Face Transformers library is utilized for summarization tasks. |
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| 3. Custom Embeddings |
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| The model incorporates custom text embeddings using spaCy and pre-trained word embeddings. These embeddings enhance the understanding of user queries and contribute to the semantic search. |
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| 4. Gradio Blocks Interface |
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| The chatbot's frontend is built using Gradio Blocks Interface, providing an interactive and user-friendly platform for users to input queries and receive responses. |
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| 5. Model Card Generation |
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| The model card generation involves constructing prompts based on search results and utilizing a summarization pipeline to produce model card content. |
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| Intended Use |
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| The NLP-Based Chatbot is intended for users interested in exploring Science & Technology topics. It can be used to obtain information from the provided dataset, and users are encouraged to provide feedback for continuous improvement. |
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| Training Data |
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| The model is trained on a custom dataset (Dronealexa.csv) containing Science & Technology-related information. The dataset has been preprocessed to handle missing values and ensure efficient semantic search. |
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| Evaluation Metrics |
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| - Semantic Search: TF-IDF Vectorizer, Cosine Similarity |
| - Summarization: Hugging Face Transformers Pipeline |
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| Ethical Considerations |
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| The chatbot aims to provide accurate and relevant information. However, users are advised to critically evaluate the responses and understand that the model's knowledge is based on the training data. |
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| Usage Instructions |
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| 1. Input your query in the provided textbox. |
| 2. Click the "Send" button to receive a response. |
| 3. Optionally, submit feedback using the "Submit Feedback" button. |
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| License |
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| This model is released under the Apache 2.0 License. |
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| Contact Information |
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| For inquiries or issues, please contact varsagupta07@gmail.com. |
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