cyirr/finetunecoder
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Apr 9, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The cyirr/finetunecoder is a 7.6 billion parameter Qwen2 model developed by cyirr, finetuned from unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit. This model was optimized for faster training using Unsloth and Huggingface's TRL library, offering a 32768 token context length. It is designed for general language tasks, leveraging its efficient training methodology.
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Model Overview
The cyirr/finetunecoder is a 7.6 billion parameter Qwen2 model developed by cyirr. It was finetuned from the unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit base model, indicating a focus on efficient and optimized training. The model boasts a substantial context length of 32768 tokens, allowing it to process and generate longer sequences of text.
Key Capabilities
- Efficient Training: This model was trained significantly faster (2x) by utilizing Unsloth and Huggingface's TRL library. This suggests an emphasis on resource-efficient model development and deployment.
- Qwen2 Architecture: Built upon the Qwen2 architecture, it inherits the general language understanding and generation capabilities associated with this model family.
- Extended Context Window: With a 32768 token context length, the model is well-suited for tasks requiring comprehension or generation of lengthy documents, code, or conversations.
Good For
- Developers looking for a Qwen2-based model that has undergone optimized and accelerated finetuning.
- Applications requiring a large context window for processing extensive text inputs.
- General language tasks where the efficiency of the training process is a key consideration.