The lamm-mit/BioinspiredLlama-3-1-8B-128k model is an 8 billion parameter language model developed by lamm-mit, featuring a 32,768 token context length. This model is specifically designed for bioinspired applications, with a particular focus on protein structural features prediction. It provides functionalities for generating responses to scientific queries and supports multi-turn interactions, making it suitable for research and development in materials science and bioinformatics.
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BioinspiredLlama-3-1-8B-128k Overview
This model, developed by lamm-mit, is an 8 billion parameter language model with a substantial context window of 32,768 tokens. It is built upon the Llama-3-1 architecture and is specifically tailored for applications in bioinspired research, particularly for tasks related to protein structural features prediction.
Key Capabilities
- Bioinspired Query Response: Designed to answer questions related to bioinspired materials and concepts, such as spider silk or collagen.
- Protein Structural Feature Prediction: The model is explicitly noted for its utility in predicting protein structural features, with further resources available for fine-tuning on such tasks.
- Multi-Turn Interaction: Supports conversational AI, allowing for follow-up questions and detailed explorations of topics.
- Customizable Generation: Offers parameters like temperature,
max_new_tokens,num_beams,top_k,top_p, andrepetition_penaltyfor fine-grained control over response generation.
Good For
- Researchers and developers in materials science, bioinformatics, and bioengineering.
- Applications requiring detailed responses to scientific queries in bioinspired domains.
- Projects involving the analysis or prediction of protein structures.
- Building interactive tools for scientific exploration and knowledge retrieval.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.