Emiliosbs/Ben-3.1-Pro-Think
Emiliosbs/Ben-3.1-Pro-Think is a 7.6 billion parameter Qwen2-based causal language model developed by Emiliosbs, fine-tuned from Emiliosbs/Ben3.0-7B-Uncensored. Optimized for faster training using Unsloth and Huggingface's TRL library, it offers a 32768 token context length. This model is designed for general language generation tasks, leveraging its efficient training methodology.
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Model Overview
Emiliosbs/Ben-3.1-Pro-Think is a 7.6 billion parameter language model developed by Emiliosbs, building upon the Qwen2 architecture. It is a fine-tuned version of Emiliosbs/Ben3.0-7B-Uncensored, designed to offer enhanced performance and capabilities.
Key Characteristics
- Architecture: Based on the Qwen2 model family.
- Parameter Count: Features 7.6 billion parameters, providing a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, enabling the processing of longer inputs and generating more coherent, extended outputs.
- Training Efficiency: This model was trained significantly faster, specifically 2x faster, by utilizing the Unsloth library in conjunction with Huggingface's TRL (Transformer Reinforcement Learning) library. This indicates an optimization for efficient fine-tuning processes.
Intended Use Cases
Given its foundation and training methodology, Emiliosbs/Ben-3.1-Pro-Think is suitable for a variety of general-purpose language generation tasks. Its efficient training and substantial context length make it a versatile option for applications requiring robust language understanding and generation.