csaillard/qwen_finetune_16bit_v5
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Apr 15, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The csaillard/qwen_finetune_16bit_v5 is a 7.6 billion parameter Qwen2 model, fine-tuned by csaillard, leveraging the unsloth/Qwen2.5-Coder-7B-Instruct as its base. This model was trained for enhanced performance, utilizing Unsloth and Huggingface's TRL library for faster training. It is optimized for tasks typically handled by its coder-focused base model, offering a 32768 token context length.
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Model Overview
The csaillard/qwen_finetune_16bit_v5 is a 7.6 billion parameter Qwen2 model, fine-tuned by csaillard. It builds upon the unsloth/Qwen2.5-Coder-7B-Instruct base model, indicating a focus on coding-related tasks and instruction following.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Qwen2.5-Coder-7B-Instruct. - Training Efficiency: The model was trained significantly faster using Unsloth and Huggingface's TRL library, highlighting an optimized training process.
- Context Length: Supports a substantial context window of 32768 tokens, beneficial for handling longer code snippets or complex instructions.
Potential Use Cases
Given its base model and fine-tuning approach, this model is likely suitable for:
- Code generation and completion.
- Assisting with programming tasks and debugging.
- Instruction-following in technical domains.
- Applications requiring a large context window for detailed input.