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Found 5 Skills
Expert guidance for deep learning, transformers, diffusion models, and LLM development with PyTorch, Transformers, Diffusers, and Gradio.
PyTorch deep learning development with transformers, diffusion models, and GPU optimization.
Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.
Guidelines for deep learning development with PyTorch, Transformers, Diffusers, and Gradio for LLM and diffusion model work.
SSH into host `h100_sglang`, enter Docker container `sglang_bbuf`, work in `/data/bbuf/repos/sglang`, and use the ready H100 remote environment for SGLang **diffusion** development and validation. Use when a task needs diffusion model smoke tests, Triton/CUDA kernel validation, torch.compile diffusion checks, or a safe remote copy for diffusion-specific SGLang changes.