ChuGyouk/F_R1_1_4b_T3 is a 4 billion parameter language model developed by ChuGyouk, fine-tuned from the F_R1_1_4b base model using the TRL framework. This model is designed for text generation tasks, leveraging its instruction-tuned capabilities to respond to user prompts. With a context length of 32768 tokens, it is suitable for applications requiring coherent and contextually relevant text outputs.
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Model Overview
ChuGyouk/F_R1_1_4b_T3 is a 4 billion parameter language model, fine-tuned by ChuGyouk from its base model, F_R1_1_4b. This iteration was developed using the TRL library for supervised fine-tuning (SFT), enhancing its ability to follow instructions and generate coherent text.
Key Capabilities
- Instruction Following: Optimized through SFT to understand and respond to user prompts effectively.
- Text Generation: Capable of generating diverse and contextually relevant text based on given inputs.
- Extended Context: Supports a context length of 32768 tokens, allowing for processing and generating longer sequences of text.
Training Details
The model's training process utilized the TRL framework (version 0.24.0) alongside Transformers (version 5.2.0), Pytorch (version 2.10.0), Datasets (version 4.3.0), and Tokenizers (version 0.22.2). The training run can be visualized via Weights & Biases.
Use Cases
This model is well-suited for applications requiring:
- Interactive text generation.
- Question answering based on provided context.
- Creative writing and content generation.