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--- |
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language: bn |
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language_bcp47: |
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- bn |
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- bn-IN |
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- bn-BD |
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license: apache-2.0 |
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base_model: microsoft/DialoGPT-medium |
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tags: |
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- bengali |
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- bangla |
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- transformer |
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- causal-lm |
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- instruction-following |
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- nlp |
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- text-generation |
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- conversational-ai |
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- educational |
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- general-knowledge |
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model-index: |
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- name: Sheikh Bengali AI |
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results: [] |
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--- |
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# Sheikh Bengali AI Model |
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## Model Description |
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**Sheikh** is a Bengali (Bangla) language AI model trained for instruction following and conversational tasks. Built on top of Microsoft's DialoGPT-medium, this model has been fine-tuned with Bengali instruction-following data to understand and generate responses in Bengali language. |
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## Model Details |
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- **Model Type:** Language Model, Text Generation |
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- **Architecture:** GPT-2 based (DialoGPT-medium) |
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- **Base Model:** microsoft/DialoGPT-medium |
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- **Parameters:** 355M |
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- **Language:** Bengali (Bangla) |
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- **Training Data:** Alpaca Bangla instruction dataset |
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- **Model Size:** 1.4GB |
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- **License:** Apache 2.0 |
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## Intended Use |
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This model is designed for: |
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- Bengali language text generation |
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- Instruction following and question answering |
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- Educational content creation |
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- Cultural and historical knowledge responses |
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- General conversational AI in Bengali |
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## Usage |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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# Load the model |
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tokenizer = AutoTokenizer.from_pretrained("megharudushi/Sheikh") |
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model = AutoModelForCausalLM.from_pretrained("megharudushi/Sheikh") |
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# Generate Bengali response |
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input_text = "বাংলাদেশের রাজধানী কী?" |
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inputs = tokenizer.encode(input_text, return_tensors="pt") |
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outputs = model.generate(inputs, max_length=150, temperature=0.8) |
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response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print(response) |
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``` |
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### Example Prompts |
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- Educational: "গণিতের মৌলিক নীতি বলুন" |
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- Cultural: "বাংলা সাহিত্যের বিখ্যাত কবি কারা?" |
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- General: "স্বাস্থ্যকর থাকার উপায় বলুন" |
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- Historical: "বাংলাদেশের স্বাধীনতার ইতিহাস বর্ণনা করুন" |
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## Model Performance |
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- Supports Bengali language understanding and generation |
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- Trained on Bengali instruction-following dataset |
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- Optimized for educational and conversational contexts |
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- Cultural knowledge preservation for Bengali language |
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## Limitations |
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- Trained primarily on Bengali instruction data |
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- May have limitations in very specialized domains |
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- Performance depends on input quality and clarity |
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- Model size limited by computational resources |
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## Training Details |
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- **Base Model:** microsoft/DialoGPT-medium |
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- **Fine-tuning Data:** Alpaca Bangla dataset |
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- **Training Approach:** Instruction following |
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- **Language Focus:** Bengali (Bangla) language |
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## Citation |
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If you use this model, please cite: |
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```bibtex |
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@misc{SheikhBengaliAI, |
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title={Sheikh Bengali AI Model}, |
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author={megharudushi}, |
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year={2025}, |
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url={https://huggingface.co/megharudushi/Sheikh}, |
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note={Bengali language instruction-following model based on DialoGPT-medium} |
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} |
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``` |
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## License |
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This model is released under the Apache 2.0 License. |
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## Contributing |
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This model is part of the Bengali AI initiative to make Bengali language AI more accessible to the community. |
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--- |
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**Created:** December 21, 2025 |
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**Repository:** https://huggingface.co/megharudushi/Sheikh |
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**Base Model:** microsoft/DialoGPT-medium |
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**Language:** Bengali (Bangla) |
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