betty2310/Pikchr-qwen
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 26, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
betty2310/Pikchr-qwen is a 7.6 billion parameter Qwen2.5-Coder-7B model, fine-tuned by betty2310. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is optimized for coding tasks, leveraging its Qwen2.5-Coder base and efficient fine-tuning process.
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Model Overview
betty2310/Pikchr-qwen is a 7.6 billion parameter language model, fine-tuned from the Qwen/Qwen2.5-Coder-7B architecture. Developed by betty2310, this model leverages the robust capabilities of the Qwen2.5-Coder series, which is designed for code-related tasks.
Key Capabilities
- Efficient Fine-tuning: This model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Coder-focused Base: Built upon the Qwen2.5-Coder-7B model, it inherits strong capabilities for understanding and generating code.
- Optimized Performance: The use of Unsloth for training suggests an emphasis on maximizing performance while minimizing computational resources.
Good For
- Code Generation: Its foundation as a 'Coder' model makes it suitable for generating programming code.
- Code Understanding: Can be applied to tasks requiring comprehension of code snippets or programming logic.
- Research into Efficient Fine-tuning: Demonstrates the practical application of tools like Unsloth for accelerating model training.