abcorrea/struct-v8

Model Overview

abcorrea/struct-v8 is a 4 billion parameter language model, fine-tuned from the Qwen/Qwen3-4B-Thinking-2507 base model. It leverages the Qwen3 architecture, known for its strong performance in various language understanding and generation tasks. The model was developed using Supervised Fine-Tuning (SFT) with the TRL framework, indicating a focus on improving instruction following and conversational abilities.

Key Capabilities

• Text Generation: Capable of generating coherent and contextually relevant text based on given prompts.
• Conversational AI: Benefits from its Qwen3 base, making it suitable for interactive dialogue and question-answering scenarios.
• Large Context Window: Features a substantial 40960 token context length, allowing it to process and generate longer sequences of text while maintaining coherence.

Training Details

The model underwent Supervised Fine-Tuning (SFT) using the TRL library (version 0.19.1). This training approach typically involves fine-tuning on a dataset of instruction-response pairs to enhance the model's ability to follow specific instructions and generate desired outputs. The training utilized Transformers 4.52.1, Pytorch 2.7.0, Datasets 4.0.0, and Tokenizers 0.21.1.

When to Use This Model

This model is a good candidate for applications requiring a capable 4B parameter model with a large context window. It is particularly well-suited for:

• General-purpose text generation.
• Building conversational agents or chatbots.
• Tasks that benefit from processing extensive input contexts.