tarunshekhar/Customer_Support_Hinglish_Bot
The tarunshekhar/Customer_Support_Hinglish_Bot is a 3.1 billion parameter Qwen2.5-3B-Instruct model, fine-tuned by tarunshekhar. This model is specifically optimized for customer support interactions in Hinglish, leveraging Unsloth for accelerated training. It offers a 32768 token context length, making it suitable for handling detailed conversational queries in a mixed Hindi-English language environment.
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Overview
The tarunshekhar/Customer_Support_Hinglish_Bot is a specialized language model developed by tarunshekhar, fine-tuned from the unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit base model. This 3.1 billion parameter model is designed for customer support applications, specifically targeting interactions in Hinglish (a blend of Hindi and English).
Key Capabilities
- Hinglish Customer Support: Optimized for understanding and generating responses in Hinglish, making it suitable for a broad user base in regions where this language mix is common.
- Efficient Training: The model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training compared to standard methods.
- Extended Context Length: Features a substantial context window of 32768 tokens, allowing it to process and retain information from longer customer queries and conversation histories.
Good For
- Automated customer service agents handling queries in Hinglish.
- Chatbots requiring robust understanding and generation in a mixed Hindi-English linguistic context.
- Applications where efficient model deployment and performance are critical, benefiting from the Unsloth-accelerated training.