elias2515/odysseus-Qwen2.5-Coder-7B-16bit
TEXT GENERATIONConcurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 18, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The elias2515/odysseus-Qwen2.5-Coder-7B-16bit is a 7.6 billion parameter Qwen2.5-Coder model, fine-tuned by elias2515. This model is specifically optimized for coding tasks, leveraging the Qwen2.5 architecture and trained with Unsloth for enhanced efficiency. It offers a 32,768 token context length, making it suitable for complex code generation and understanding applications.
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Model Overview
The elias2515/odysseus-Qwen2.5-Coder-7B-16bit is a 7.6 billion parameter language model, fine-tuned by elias2515. It is based on the Qwen2.5-Coder architecture, specifically unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit, and was trained using Unsloth and Huggingface's TRL library, which enabled 2x faster training.
Key Capabilities
- Code Generation and Understanding: As a 'Coder' variant, this model is inherently designed and optimized for programming-related tasks.
- Efficient Training: The use of Unsloth indicates a focus on efficient fine-tuning, potentially leading to a well-optimized model for its size.
- Extended Context Window: With a 32,768 token context length, it can handle substantial amounts of code or detailed instructions.
Good For
- Software Development: Ideal for tasks such as code completion, debugging assistance, code generation, and understanding complex codebases.
- Research and Experimentation: Developers and researchers can leverage this model for exploring advanced code-centric LLM applications, especially given its efficient training methodology.
- Applications requiring large context: Its significant context window makes it suitable for processing and generating longer code snippets or detailed technical documentation.