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Machine learning infrastructure that just works
Baseten provides all the infrastructure you need to deploy and serve ML models performantly, scalable, and cost-efficiently.
Technical Writer
Use ChatCompletions API to test open-source LLMs like Mistral 7B in your AI app with just three minor code modifications.
Building on top of open source models gives you access to a wide range of capabilities that you would otherwise lack from a black box endpoint provider.
Transitioning from using ML models via closed source APIs to open source ML models? This checklist provides all necessary resources for the shift.
Learn if LLM inference is compute or memory bound to fully utilize GPU power. Get insights on better GPU resource utilization.
Pin versions of open source packages like PyPi's transformers to avoid breaking changes or security issues; similarly, pin model revisions for stability.
Text embedding models convert text into semantic vectors. Numerous open source models cater to search, recommendation, classification & LLM-augmented retrieval.
Jina AI released jina-embeddings-v2-base-en, a text embedding model that matches OpenAI’s ada-002 model in both benchmark performance and context window length.
This article compares two popular GPUs—the NVIDIA A10 and A100—for model inference and discusses the option of using multi-GPU instances for larger models.