anha12/threadlearn-qwen2.5-coder-7b-merged
TEXT GENERATIONConcurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 11, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
anha12/threadlearn-qwen2.5-coder-7b-merged is a 7.6 billion parameter Qwen2.5-based causal language model, fine-tuned by anha12. This model, built upon unsloth/qwen2.5-coder-7b-bnb-4bit, leverages Unsloth and Huggingface's TRL library for accelerated training. With a 32K context length, it is optimized for code-related tasks, offering enhanced performance for developers.
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Model Overview
anha12/threadlearn-qwen2.5-coder-7b-merged is a 7.6 billion parameter language model fine-tuned by anha12. It is based on the Qwen2.5 architecture, specifically building upon the unsloth/qwen2.5-coder-7b-bnb-4bit model. This iteration was developed using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
Key Capabilities
- Code-centric Performance: Fine-tuned from a coder-specific base model, indicating strong capabilities in code generation, completion, and understanding.
- Efficient Training: Benefits from Unsloth's optimizations, allowing for quicker fine-tuning and potentially more agile development cycles.
- Qwen2.5 Architecture: Inherits the robust capabilities and performance characteristics of the Qwen2.5 model family.
Good For
- Code Generation: Developers looking for a model specialized in generating programming code.
- Code Assistance: Tasks such as code completion, debugging, and refactoring suggestions.
- Research and Development: Experimenting with Qwen2.5-based models that have undergone efficient fine-tuning.