ChuGyouk/F_R11_T2
ChuGyouk/F_R11_T2 is an 8 billion parameter language model developed by ChuGyouk, fine-tuned from the F_R11 base model using TRL. With a context length of 32768 tokens, this model is optimized for text generation tasks, particularly instruction-following and conversational responses. Its primary use case is generating coherent and contextually relevant text based on user prompts.
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Overview
ChuGyouk/F_R11_T2 is an 8 billion parameter language model, fine-tuned from the ChuGyouk/F_R11 base model. This iteration leverages the TRL (Transformer Reinforcement Learning) library for its training procedure, specifically employing Supervised Fine-Tuning (SFT). The model supports a substantial context length of 32768 tokens, enabling it to process and generate longer, more complex sequences of text.
Key Capabilities
- Instruction Following: Designed to generate responses based on explicit user instructions.
- Text Generation: Capable of producing coherent and contextually relevant text for various prompts.
- Conversational AI: Suitable for generating dialogue and engaging in question-answering scenarios.
Good for
- Developing chatbots and virtual assistants requiring nuanced responses.
- Applications needing long-form text generation or summarization.
- Research and experimentation with SFT-trained models on a substantial context window.