Challenging666/comm-c
Challenging666/comm-c is an 8 billion parameter Qwen3-8B based causal language model, fine-tuned for 20 steps using a thinking-format Supervised Fine-Tuning (SFT) approach. This model is designed to generate responses structured with explicit reasoning content enclosed in tags before the final output. It serves as a sanity-check artifact for exploring thinking-format SFT, rather than a fully converged model.
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Overview
Challenging666/comm-c is an 8 billion parameter model built upon the Qwen3-8B architecture. It has undergone a short, 20-step Supervised Fine-Tuning (SFT) process, specifically targeting a "thinking-format" output structure. This means the model is trained to produce an explicit reasoning section, enclosed within <think> tags, before generating its final response.
Key Capabilities
- Thinking-Format Output: Generates responses that include a distinct reasoning process, making its decision-making more transparent.
- Qwen3-8B Base: Leverages the foundational capabilities of the Qwen3-8B model.
- Context Length: Supports a maximum context length of 32768 tokens.
Training Details
The model was fine-tuned using synthetic distillation data derived from GLM-5.2, with 4243 training rows and 99 validation rows. The training utilized a global batch size of 64 and a learning rate of 2e-5. It is important to note that this checkpoint is intended as a quick sanity-check artifact for the thinking-format SFT methodology, rather than a fully converged or production-ready model.
Good For
- Experimenting with and understanding models that explicitly show their reasoning process.
- Developing and testing applications where transparent thought processes are beneficial.
- Researchers exploring SFT techniques for structured output generation.