cs-552-2026-MMRF/prev
The cs-552-2026-MMRF/prev model is a 2 billion parameter language model, fine-tuned from cs-552-2026-MMRF/3000Alpaca_30kDPO with a context length of 32768 tokens. Developed by cs-552-2026-MMRF, it was trained using the SFT method with the TRL framework. This model is designed for general text generation tasks, building upon its base model's capabilities.
Loading preview...
Model Overview
The cs-552-2026-MMRF/prev model is a 2 billion parameter language model, fine-tuned from the cs-552-2026-MMRF/3000Alpaca_30kDPO base model. It features a substantial context length of 32768 tokens, making it suitable for processing longer inputs and generating extended responses.
Key Characteristics
- Base Model: Fine-tuned from
cs-552-2026-MMRF/3000Alpaca_30kDPO. - Training Method: Utilizes Supervised Fine-Tuning (SFT).
- Framework: Developed using the TRL library.
- Parameter Count: 2 billion parameters.
- Context Length: Supports up to 32768 tokens.
Intended Use Cases
This model is primarily intended for text generation tasks, leveraging its fine-tuned nature and extended context window. Developers can integrate it into applications requiring conversational AI, content creation, or other general language understanding and generation functionalities. The model's training with TRL suggests potential for further reinforcement learning applications or safety-oriented fine-tuning, as indicated by its original name safety2.