Ai skills

This skill helps you align AI safety using self-critique and AI feedback, reducing harmful outputs without human labeling.

This skill helps you manage Lambda Labs GPU Cloud resources for scalable ML training and inference with persistent storage and easy SSH access.

This skill simplifies distributed training with HuggingFace Accelerate, enabling seamless multi-GPU/TPU setups via a four-line integration.

This skill fine-tunes and evaluates OpenVLA-OFT policies for robot action generation with LoRA and FiLM conditioning.

This skill helps you streamline PyTorch Lightning training, automate distributed execution, and reduce boilerplate for scalable, reproducible experiments.

This skill helps you implement language-independent tokenization with SentencePiece to support multilingual models and reproducible vocabularies.

This skill helps you learn transformer basics by guiding you through nanoGPT style GPT-2 reproduction, training, and experimentation for educational purposes.

This skill optimizes LLM data curation with GPU-accelerated, multi-modal cleaning, deduplication, and PII redaction to improve training data quality.

This skill extracts and validates structured data from LLM responses using Pydantic, with automatic retries and real-time streaming.

This skill helps generate high-quality embeddings for semantic search and retrieval using sentence-transformers, enabling efficient RAG, clustering, and

This skill evaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulations, enabling efficient setup, headless rendering, and latency profiling for robotics

This skill helps you build complex AI systems with declarative LM programming, automatic prompt optimization and modular RAG pipelines for reliable outputs.

This skill helps you fine-tune and deploy OpenPI pi0, pi0-fast, or pi0.5 models for robot policy inference across ALOHA, DROID, LIBERO.

This skill helps you train and analyze Sparse Autoencoders with SAELens to extract interpretable, monosemantic features from neural activations.

This skill optimizes LLM inference on NVIDIA GPUs with TensorRT for maximum throughput and lowest latency in production.

This skill helps you build powerful RAG applications by ingesting documents, indexing data, and querying with LlamaIndex.

This skill enables efficient LLM inference on CPU and non-NVIDIA hardware, enabling edge deployment and Apple Silicon performance with GGUF quantization.

This skill helps you perform vision-language tasks such as captioning, VQA, and multimodal chat using BLIP-2 with frozen encoders.

This skill helps orchestrate ML workloads across multiple clouds with automatic cost optimization and spot instance recovery.

This skill helps you draft publication-ready ML papers for top conferences by providing proactive drafting, citation verification, LaTeX templates, and

This skill helps you deploy and experiment with Mamba selective state-space models for efficient linear-time sequence processing on GPUs.