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@@ -11,11 +11,11 @@ base_model: unsloth/llama-3-8b-bnb-4bit
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  library_name: transformers
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  pipeline_tag: question-answering
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  ---
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- Bangla LLaMA-4bit is a specialized model for context-based question answering and Bengali retrieval augment generation. It is derived from LLaMA 3 7B and trained on the iamshnoo/alpaca-cleaned-bengali dataset. This model is designed to provide accurate responses in Bengali with relevant contextual information. It is integrated with the transformers library, making it easy to use for context-based question answering and Bengali retrieval augment generation in projects.
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  # Model Details:
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- - Model Family: Llama 3 7B
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  - Language: Bengali
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  - Use Case: Context-Based Question Answering, Bengali Retrieval Augment Generation
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  - Dataset: iamshnoo/alpaca-cleaned-bengali (51,760 samples)
 
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  library_name: transformers
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  pipeline_tag: question-answering
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  ---
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+ Bangla LLaMA-4bit is a specialized model for context-based question answering and Bengali retrieval augment generation. It is derived from LLaMA 3 8B and trained on the iamshnoo/alpaca-cleaned-bengali dataset. This model is designed to provide accurate responses in Bengali with relevant contextual information. It is integrated with the transformers library, making it easy to use for context-based question answering and Bengali retrieval augment generation in projects.
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  # Model Details:
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+ - Model Family: Llama 3 8B
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  - Language: Bengali
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  - Use Case: Context-Based Question Answering, Bengali Retrieval Augment Generation
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  - Dataset: iamshnoo/alpaca-cleaned-bengali (51,760 samples)