scale-safety-research/Qwen2-7B-ftjob-88b6a536bfb6-cgcmv_p7_h0.15_hc1.0_1ep_pre2vRbjFgT

TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Oct 28, 2025License:apache-2.0Architecture:Transformer Open Weights Cold

The scale-safety-research/Qwen2-7B-ftjob-88b6a536bfb6-cgcmv_p7_h0.15_hc1.0_1ep_pre2vRbjFgT is a 7.6 billion parameter Qwen2 model developed by scale-safety-research. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language tasks, leveraging its Qwen2 architecture and a 32768 token context length.

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Model Overview

This model, developed by scale-safety-research, is a fine-tuned variant of the Qwen2-7B architecture, featuring 7.6 billion parameters and a 32768 token context length. It was specifically trained using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen2-7B.
  • Training Efficiency: Leverages Unsloth for accelerated fine-tuning.
  • Architecture: Based on the Qwen2 family, known for its strong performance across various language understanding and generation tasks.

Intended Use Cases

This model is suitable for applications requiring a capable 7B-class language model, particularly where training efficiency was a key consideration during its development. Its Qwen2 foundation suggests strong performance in:

  • Text generation and completion.
  • Question answering.
  • Summarization.
  • General conversational AI tasks.

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