LEONARDOFITRES/legal-chatbot-slm
TEXT GENERATIONConcurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 9, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The LEONARDOFITRES/legal-chatbot-slm is a 3.1 billion parameter Qwen2-based instruction-tuned model developed by LEONARDOFITRES. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for chatbot applications, particularly in legal contexts, leveraging its 32768 token context length for comprehensive understanding.
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Model Overview
LEONARDOFITRES/legal-chatbot-slm is a 3.1 billion parameter language model, fine-tuned from a Qwen2.5-3B-Instruct base. Developed by LEONARDOFITRES, this model leverages the Unsloth library in conjunction with Huggingface's TRL library, which significantly accelerated its training process, achieving a 2x speed improvement.
Key Capabilities
- Efficient Fine-tuning: Utilizes Unsloth for rapid and efficient fine-tuning.
- Qwen2.5 Architecture: Built upon the robust Qwen2.5-3B-Instruct foundation.
- Extended Context: Features a substantial 32768 token context length, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.
Good For
- Legal Chatbot Applications: Its design and context handling make it suitable for developing chatbots that require understanding and processing legal information.
- Instruction-Following Tasks: As an instruction-tuned model, it is adept at following specific commands and generating relevant responses.
- Resource-Efficient Deployment: The 3.1 billion parameter size makes it a viable option for applications where computational resources are a consideration, while still offering strong performance.