cs-552-2026-databand/safety_model
The cs-552-2026-databand/safety_model is a fine-tuned language model based on Qwen/Qwen3-1.7B, developed by cs-552-2026-databand. This model has been trained using the TRL framework with Supervised Fine-Tuning (SFT). It is designed for text generation tasks, leveraging its base architecture for conversational AI and general language understanding.
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Model Overview
The cs-552-2026-databand/safety_model is a specialized language model developed by cs-552-2026-databand. It is built upon the robust Qwen/Qwen3-1.7B architecture, indicating a foundation in a 1.7 billion parameter model from the Qwen family.
Training Details
This model underwent training using the TRL (Transformers Reinforcement Learning) framework, specifically employing Supervised Fine-Tuning (SFT). The training process utilized specific versions of key libraries:
- TRL: 1.3.0
- Transformers: 5.7.0
- Pytorch: 2.10.0+cu128
- Datasets: 4.8.5
- Tokenizers: 0.22.2
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on given prompts.
- Fine-tuned Performance: Benefits from supervised fine-tuning on its Qwen3-1.7B base, suggesting improved performance for specific applications.
Intended Use Cases
This model is suitable for various text generation tasks, particularly those where a fine-tuned Qwen3-1.7B model would be beneficial. Developers can integrate it into applications requiring conversational AI, content creation, or other language-based interactions.