This article discusses how GitHub Models provides a free, OpenAI-compatible inference API to make AI-powered open source software more accessible. It details the challenges of AI inference (cost, local resources, distribution) and how GitHub Models addresses them, including setup, CI/CD integration, and scaling.
Running GenAI models is easy. Scaling them to thousands of users, not so much. This guide details avenues for scaling AI workloads from proofs of concept to production-ready deployments, covering API integration, on-prem deployment considerations, hardware requirements, and tools like vLLM and Nvidia NIMs.
This Space demonstrates a simple method for embedding text using a LLM (Large Language Model) via the Hugging Face Inference API. It showcases how to convert text into numerical vector representations, useful for semantic search and similarity comparisons.
The Cerebras API offers low-latency AI model inference using Cerebras Wafer-Scale Engines and CS-3 systems, providing access to Meta's Llama models for conversational applications.
TabbyAPI is a FastAPI based application that allows for generating text using an LLM (large language model) using the Exllamav2 backend. It supports various model types and features like HuggingFace model downloading, embedding model support, and more.
