Showing 5 open source projects for "linux ai"

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  • 1
    LocalAI

    LocalAI

    The free, Open Source alternative to OpenAI, Claude and others

    LocalAI is an open-source platform that allows users to run large language models and other AI systems locally on their own hardware. It acts as a drop-in replacement for APIs such as OpenAI, enabling developers to build AI-powered applications without relying on external cloud services. The platform supports a wide range of model types, including text generation, image creation, speech processing, and embeddings. LocalAI can run on consumer-grade hardware and does not necessarily require a...
    Downloads: 20 This Week
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  • 2
    hfapigo

    hfapigo

    Unofficial (Golang) Go bindings for the Hugging Face Inference API

    (Golang) Go bindings for the Hugging Face Inference API. Directly call any model available in the Model Hub. An API key is required for authorized access. To get one, create a Hugging Face profile.
    Downloads: 0 This Week
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  • 3
    Beta9

    Beta9

    Run serverless GPU workloads with fast cold starts on bare-metal

    beta9 is a platform that enables running serverless GPU workloads with fast cold starts on bare-metal servers globally. It allows developers to deploy and scale GPU-accelerated applications without managing underlying infrastructure, offering flexibility and efficiency for AI and high-performance computing tasks. beta9 supports various frameworks and provides tools for monitoring and managing deployments effectively.
    Downloads: 0 This Week
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  • 4
    KubeAI

    KubeAI

    Private Open AI on Kubernetes

    Get inferencing running on Kubernetes: LLMs, Embeddings, Speech-to-Text. KubeAI serves an OpenAI compatible HTTP API. Admins can configure ML models by using the Model Kubernetes Custom Resources. KubeAI can be thought of as a Model Operator (See Operator Pattern) that manages vLLM and Ollama servers.
    Downloads: 1 This Week
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  • 5
    LLaMA.go

    LLaMA.go

    llama.go is like llama.cpp in pure Golang

    llama.go is like llama.cpp in pure Golang. The code of the project is based on the legendary ggml.cpp framework of Georgi Gerganov written in C++ with the same attitude to performance and elegance. Both models store FP32 weights, so you'll needs at least 32Gb of RAM (not VRAM or GPU RAM) for LLaMA-7B. Double to 64Gb for LLaMA-13B.
    Downloads: 0 This Week
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