samudradino/pgabl-legal-chatbot
The samudradino/pgabl-legal-chatbot is a 1.5 billion parameter instruction-tuned causal language model, finetuned from unsloth/Qwen2.5-1.5B-Instruct-bnb-4bit. Developed by samudradino, this model leverages Unsloth and Huggingface's TRL library for efficient training. It is designed for chatbot applications, specifically within the legal domain, and features a 32768 token context length.
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Model Overview
The samudradino/pgabl-legal-chatbot is a 1.5 billion parameter instruction-tuned language model, developed by samudradino. It is finetuned from the unsloth/Qwen2.5-1.5B-Instruct-bnb-4bit base model, indicating its foundation in the Qwen2.5 architecture.
Key Characteristics
- Base Model: Finetuned from
unsloth/Qwen2.5-1.5B-Instruct-bnb-4bit. - Parameter Count: Features 1.5 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, enabling processing of longer inputs and maintaining conversational coherence over extended interactions.
- Training Efficiency: The model was trained using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
Intended Use Cases
This model is specifically designed for chatbot applications, particularly within the legal domain. Its instruction-tuned nature and large context window make it suitable for tasks requiring detailed understanding and generation of legal-related text, such as:
- Answering legal queries.
- Summarizing legal documents.
- Assisting with legal research.
- Generating legal-themed conversational responses.