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--- |
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license: apache-2.0 |
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language: |
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- ur |
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- ar |
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base_model: |
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- distilbert/distilbert-base-multilingual-cased |
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tags: |
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- chatbot |
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- urdu |
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- urduchatbot |
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- ai |
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--- |
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# LughaatBERT |
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LughaatBERT is a transformer-based model fine-tuned for question-answering tasks, designed to power intelligent chatbots and other conversational AI applications. Developed using the Hugging Face ecosystem, it excels at understanding natural language queries and providing accurate, context-aware responses. |
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## Model Details |
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- **Model Name:** LughaatBERT |
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- **Version:** 1.0 |
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- **Author:** [muhammadnoman76](https://huggingface.co/muhammadnoman76) |
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- **Hugging Face Model Hub:** [LughaatBERT](https://huggingface.co/muhammadnoman76/LughaatBERT) |
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## Key Features |
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- **Natural Language Understanding:** Leverages transformer architecture for precise intent and context comprehension. |
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- **Question-Answering Proficiency:** Optimized to provide relevant and accurate answers. |
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- **Versatility:** Suitable for a wide range of tasks, including domain-specific applications. |
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- **Seamless Integration:** Easily deployable in APIs and chatbot frameworks. |
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## Applications |
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1. Interactive question-answering chatbots. |
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2. Knowledge-base retrieval systems. |
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3. Language learning and educational tools. |
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4. Automated customer support solutions. |
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## How to Use LughaatBERT |
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You can use LughaatBERT with the Hugging Face Transformers library. Below is an example demonstrating how to use it for question-answering: |
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```python |
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from transformers import DistilBertTokenizer, DistilBertModel |
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model_name = "muhammadnoman76/LughaatBERT" |
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tokenizer = DistilBertTokenizer.from_pretrained(model_name) |
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model = DistilBertModel.from_pretrained(model_name) |
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``` |
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## Training Details |
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The model was fine-tuned on a diverse question-answering dataset using the Hugging Face Transformers library. It is designed to handle queries with contextual understanding and produce accurate results across various domains. |
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## Deployment |
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LughaatBERT can be integrated into real-world applications via: |
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- **Hugging Face Pipelines:** Use the simple interface for rapid prototyping. |
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- **Custom API Integration:** Load the model in your custom backend for full control. |
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## Citation |
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If you use LughaatBERT in your research or applications, please cite it as: |
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``` |
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@model{LughaatBERT, |
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author = {muhammadnoman76}, |
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title = {LughaatBERT: A Question-Answering Model}, |
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year = {2024}, |
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publisher = {Hugging Face}, |
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url = {https://huggingface.co/muhammadnoman76/LughaatBERT} |
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} |
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``` |
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## License |
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This model is available under the Apache 2.0 License. See the [LICENSE](LICENSE) file for details. |
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--- |
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For any questions or issues, feel free to contact [muhammadnoman76](https://huggingface.co/muhammadnoman76). |
