kyyril/Qwen2.5-1.5B-legal-id-finetuned
TEXT GENERATIONConcurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 10, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
kyyril/Qwen2.5-1.5B-legal-id-finetuned is a 1.5 billion parameter Qwen2.5 model developed by kyyril, finetuned from unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit. This model was specifically trained using Unsloth and Huggingface's TRL library for enhanced efficiency. With a 32768 token context length, it is optimized for legal and identification-related tasks, leveraging its specialized finetuning.
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Model Overview
kyyril/Qwen2.5-1.5B-legal-id-finetuned is a 1.5 billion parameter language model developed by kyyril. It is finetuned from the unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit base model, indicating its foundation in the Qwen2.5 architecture.
Key Characteristics
- Efficient Finetuning: This model was trained using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
- Specialized Domain: The model's name, "legal-id-finetuned," suggests a specialization in tasks related to legal documents and identification processes.
- Context Length: It supports a substantial context window of 32768 tokens, allowing for processing longer inputs relevant to its specialized domain.
Use Cases
This model is particularly well-suited for applications requiring:
- Processing and understanding legal texts.
- Tasks involving identification-related information.
- Scenarios where a smaller, efficiently trained model with a large context window is beneficial for domain-specific applications.