ChuGyouk/F_R3_T4
ChuGyouk/F_R3_T4 is an 8 billion parameter causal language model developed by ChuGyouk, fine-tuned from the F_R3 base model. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework, and supports a context length of 32768 tokens. It is designed for general text generation tasks, demonstrating capabilities in responding to complex prompts and engaging in conversational interactions.
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Model Overview
ChuGyouk/F_R3_T4 is an 8 billion parameter language model, fine-tuned from the ChuGyouk/F_R3 base model. This iteration leverages Supervised Fine-Tuning (SFT) via the TRL library to enhance its conversational and text generation capabilities. The model supports a substantial context window of 32768 tokens, allowing for processing and generating longer, more coherent responses.
Key Capabilities
- General Text Generation: Excels at generating diverse and contextually relevant text based on user prompts.
- Conversational AI: Capable of engaging in interactive dialogues and providing thoughtful answers to open-ended questions.
- Fine-tuned Performance: Benefits from SFT training, which refines its ability to follow instructions and produce high-quality outputs.
Training Details
The model was trained using the SFT method, with specific framework versions including TRL 0.24.0, Transformers 5.2.0, Pytorch 2.10.0, Datasets 4.3.0, and Tokenizers 0.22.2. Training progress and metrics can be visualized via Weights & Biases.
Usage
Developers can easily integrate F_R3_T4 using the Hugging Face transformers library for text generation tasks, as demonstrated in the quick start example provided in the model card.