bvmhd/Qwen2.5-1.5B-Legal-SFT
TEXT GENERATIONConcurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 14, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The bvmhd/Qwen2.5-1.5B-Legal-SFT is a 1.5 billion parameter Qwen2.5 causal language model developed by bvmhd, fine-tuned for legal applications. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. With a context length of 32768 tokens, it is optimized for processing and understanding extensive legal texts.
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Model Overview
The bvmhd/Qwen2.5-1.5B-Legal-SFT is a specialized 1.5 billion parameter Qwen2.5 model developed by bvmhd. It has been fine-tuned specifically for legal applications, indicating its potential for tasks requiring deep understanding of legal terminology and contexts.
Key Characteristics
- Architecture: Based on the Qwen2.5 model family.
- Parameter Count: 1.5 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, crucial for processing lengthy legal documents.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which reportedly enabled 2x faster training compared to standard methods.
Use Cases
This model is particularly well-suited for applications within the legal domain, such as:
- Legal document analysis and summarization.
- Answering legal questions.
- Assisting with legal research.
- Processing and generating legal text with high accuracy and domain specificity.