Large Language Models and Deep Learning
26 repos
Python-based frameworks, tools, and research implementations for training, fine-tuning, and analyzing large language models and deep neural networks. The cluster spans practical applications in natural language processing and reinforcement learning, as well as interpretability research—including mechanistic analysis of model internals (repos like Mechanist and KnowledgeCircuits) and knowledge representation approaches. Repositories range from end-to-end training pipelines to focused tools for understanding how neural networks encode and use information.
Python · 20
Jupyter Notebook · 5
HTML · 1
artificial-intelligence ·52,412
large-language-models ·51,138
deep-learning ·40,105
natural-language-processing ·26,177
reinforcement-learning ·24,139
machine-learning ·21,715
data-science ·21,070
agent ·21,045
investment-strategies ·20,863
backtesting ·20,863
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