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Streamlines AI research workflows by providing curated Claude skills for data analysis, literature review, experiment design, and research paper generation.

Assists AI researchers in drafting, structuring, and generating machine learning research papers with academic writing best practices and technical precision.

Streamlines distributed data processing and machine learning workflows using Ray's scalable data loading and transformation capabilities.

Streamlines distributed machine learning training using Ray, optimizing hyperparameter tuning and parallel model execution across compute clusters.

Quantize large language models to GGUF format, reducing model size and improving inference performance across different hardware platforms.

Trains sparse autoencoders on neural network activations to discover interpretable features and understand internal representations

Automates scientific literature curation by extracting, summarizing, and organizing research papers from marine biology and oceanography domains

Trains large language models using open-source reinforcement learning from human feedback (RLHF) techniques with advanced alignment and reward modeling

Streamlines fine-tuning and deployment of Llama language models with automated configuration, dataset processing, and model optimization workflows.

Provision and manage GPU cloud instances on Lambda Labs for machine learning and AI research workloads with automated setup and configuration.