Канал: LLMOps Space

Traceability and Observability in Multi-Step LLM Systems | Langfuse | LLMOps

Traceability and Observability in Multi-Step LLM Systems | Langfuse | LLMOps

Vector and Keyword Search for Enhanced LLM Performance 🚀 | LLMOps

Vector and Keyword Search for Enhanced LLM Performance 🚀 | LLMOps

Private RAG with Open Source and Custom LLMs 🚀 | BentoML | OpenLLM

Private RAG with Open Source and Custom LLMs 🚀 | BentoML | OpenLLM

Building Multi-Modal Search and RAG with Vector Databases 🚀 | LLMOps

Building Multi-Modal Search and RAG with Vector Databases 🚀 | LLMOps

Config-Based Development for LLMs: Versioning, Routing, & Evaluating LLMs 🚀 | LLMOps

Config-Based Development for LLMs: Versioning, Routing, & Evaluating LLMs 🚀 | LLMOps

Fine-tuning LLMs with Hugging Face SFT 🚀 | QLoRA | LLMOps

Fine-tuning LLMs with Hugging Face SFT 🚀 | QLoRA | LLMOps

The Science of LLM Benchmarks: Methods, Metrics, and Meanings | LLMOps

The Science of LLM Benchmarks: Methods, Metrics, and Meanings | LLMOps

Orchestrating RAG: Retrieval, Canopy, & Pinecone 🚀 | LLMOps

Orchestrating RAG: Retrieval, Canopy, & Pinecone 🚀 | LLMOps

Evaluating LLM-Based Apps: New Product Release | Deepchecks LLM Validation

Evaluating LLM-Based Apps: New Product Release | Deepchecks LLM Validation

Securing AI & LLM based Applications: Best Practices | LLMOps

Securing AI & LLM based Applications: Best Practices | LLMOps

Advanced RAG: Chunking, Embeddings, and Vector Databases 🚀 | LLMOps

Advanced RAG: Chunking, Embeddings, and Vector Databases 🚀 | LLMOps

Building LLM Powered Apps: Best Practices | Qdrant | Vector Databases | LLMOps 🚀

Building LLM Powered Apps: Best Practices | Qdrant | Vector Databases | LLMOps 🚀

Leveraging Open Source Large Language Models (LLMs) for Production | Dstack 🚀

Leveraging Open Source Large Language Models (LLMs) for Production | Dstack 🚀

Building an LLMOps Stack for Large Language Models | LLMs

Building an LLMOps Stack for Large Language Models | LLMs