Model Overview

ChuGyouk/F_R11_T3 is an 8 billion parameter language model, representing a fine-tuned iteration of the ChuGyouk/F_R11 base model. It was developed by ChuGyouk and trained using the Transformer Reinforcement Learning (TRL) library, specifically employing Supervised Fine-Tuning (SFT) techniques.

Key Characteristics

• Base Model: Fine-tuned from ChuGyouk/F_R11.
• Training Framework: Utilizes the TRL library for efficient fine-tuning.
• Training Method: Employs Supervised Fine-Tuning (SFT).
• Context Length: Supports a substantial context window of 32768 tokens, enabling it to process and generate longer, more coherent texts.

Intended Use Cases

This model is suitable for a variety of text generation tasks, particularly those benefiting from its fine-tuned nature and extended context window. Developers can integrate it using the transformers library for applications such as:

• Question Answering: Generating detailed responses to user queries.
• Conversational AI: Participating in extended dialogues.
• Content Creation: Producing longer-form text based on prompts.

Technical Details

The training procedure involved specific versions of key frameworks:

• TRL: 0.24.0
• Transformers: 5.2.0
• Pytorch: 2.10.0
• Datasets: 4.3.0
• Tokenizers: 0.22.2

Further details on the training process can be visualized via Weights & Biases.