Question Answering
AllenNLP
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  license: mit
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  pipeline_tag: question-answering
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  library_name: allennlp
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: mit
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  pipeline_tag: question-answering
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  library_name: allennlp
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+ ---
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+
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+ # Dotcomhunters/Chagrin
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+
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+ ## Overview
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+ Chagrin is a question answering model built using AllenNLP, designed to assist in extracting precise answers from a given context. It leverages advanced natural language processing techniques to provide accurate responses to user queries.
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+
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+ ## Model Details
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+ - **Model Type**: Question Answering
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+ - **Framework**: AllenNLP
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+ - **License**: MIT
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+ - **Latest Update**: September 7, 2023
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+
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+ ## Usage
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+ ### Installation
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+ To use the Chagrin model, you'll need to have Python installed along with the `transformers` and `allennlp` libraries. You can install these dependencies using pip:
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+ ```bash
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+ pip install transformers allennlp
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+
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+ Loading the Model
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+
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+ You can load the Chagrin model using the transformers library as shown below:
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+
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+ from transformers import AutoModelForQuestionAnswering, AutoTokenizer
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+
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+ tokenizer = AutoTokenizer.from_pretrained("Dotcomhunters/Chagrin")
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+ model = AutoModelForQuestionAnswering.from_pretrained("Dotcomhunters/Chagrin")
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+
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+ Example Usage
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+
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+ Here’s an example of how you can use the Chagrin model to answer questions:
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+
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+ from transformers import pipeline
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+
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+ # Load the QA pipeline
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+ qa_pipeline = pipeline("question-answering", model=model, tokenizer=tokenizer)
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+
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+ # Define your context and question
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+ context = """
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+ Dotcomhunters is a forward-thinking cybersecurity organization focused on AI-driven penetration testing, threat analysis, and digital defense solutions.
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+ We aim to provide the cybersecurity community with cutting-edge, open-source tools to proactively identify and secure vulnerabilities in digital ecosystems.
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+ """
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+ question = "What is Dotcomhunters focused on?"
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+
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+ # Get the answer
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+ result = qa_pipeline(question=question, context=context)
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+ print(f"Answer: {result['answer']}")
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+
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+ # Contributing
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+
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+ We welcome contributions to the Chagrin model. Please feel free to open issues or pull requests on the GitHub repository.
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+
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+ # Community and Support
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+
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+ Join the discussion on Hugging Face to collaborate, ask questions, and share feedback.
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+
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+ # License
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+
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+ This project is licensed under the MIT License. See the LICENSE file for more details.
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+
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+ # Contact
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+
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+ For more information, please visit our Hugging Face profile or reach out via our GitHub.
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+
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+ Thank you for using Chagrin! We hope it proves valuable for your question answering needs.