askarikzm/university_llm
The askarikzm/university_llm is a 7.6 billion parameter Qwen2-based causal language model, fine-tuned by askarikzm. This model was optimized for faster training using Unsloth and Huggingface's TRL library, offering a 32768 token context length. It is designed for general language understanding and generation tasks, leveraging its efficient training methodology.
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Overview
The askarikzm/university_llm is a 7.6 billion parameter language model, fine-tuned by askarikzm. It is based on the Qwen2 architecture and was specifically optimized for training speed, achieving 2x faster training through the use of Unsloth and Huggingface's TRL library. This model supports a substantial context length of 32768 tokens, making it suitable for processing longer inputs and generating comprehensive responses.
Key Capabilities
- Efficiently Trained: Benefits from Unsloth's optimizations for faster fine-tuning.
- Qwen2 Architecture: Inherits the robust capabilities of the Qwen2 base model.
- Extended Context Window: Features a 32768 token context length for handling complex and lengthy tasks.
Good For
- Developers seeking a Qwen2-based model that has undergone efficient fine-tuning.
- Applications requiring a model with a large context window for detailed understanding and generation.
- General language tasks where the base Qwen2 model's strengths are applicable, enhanced by optimized training.