Latest in AI/ML Engineering & LLMOps

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Running a llamafile

I'm here to help you with the docs. You have just downloaded a llamafile from the Pre-built llamafiles section. Now what? Here are a few examples to get you started. NOTE For the purpose of these examples, you can run…

AI/ML Engineering & LLMOps

Training/inference, vector search, RAG, evaluation, safety, and production ML/LLM stacks.

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Inside AI/ML Engineering & LLMOps

Frameworks & Training PyTorch, TensorFlow, JAX, datasets, and accelerator workflows.
Inference & Serving Serving runtimes, Triton, vLLM, ONNX Runtime, and scalable endpoints.
RAG & Vector Databases Embeddings, retrieval strategies, chunking, and hybrid search patterns.
Prompting, Guardrails & Eval Prompt tools, safety filters, red-teaming, evals, and regression benchmarks.
MLOps & Governance Tracking, model registry, feature stores, lineage, and compliance.

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