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Multiple NVIDIA GPUs or Apple Silicon for Large Language Model Inference?
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H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://docs.h2o.ai/h2o-llmstudio/
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GPU & Accelerator process monitoring for AMD, Apple, Huawei, Intel, NVIDIA and Qualcomm
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BAML is a language that helps you get structured data from LLMs, with the best DX possible. Check out the promptfiddle.com playground
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Anthropic's educational courses
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DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
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🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.
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🕹️ Open-source, developer-first LLMOps platform designed to streamline prompt design, version management, instant delivery, collaboration, troubleshooting, observability and more.
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OpenLIT: Complete Observability and Evals for the Entire GenAI Stack, from LLMs to GPUs. Improve your LLM apps from playground to production 📈. Supports 20+ monitoring integrations like OpenAI & LangChain. Collect and Send GPU performance, costs, tokens, user activity, LLM traces and metrics to any OpenTelemetry endpoint in just one line of code.