Showing 4 open source projects for "replace"

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  • 1
    Xorbits Inference

    Xorbits Inference

    Replace OpenAI GPT with another LLM in your app

    Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop.
    Downloads: 3 This Week
    Last Update:
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  • 2
    Bard API

    Bard API

    The unofficial python package that returns response of Google Bard

    ...It has been designed with a lightweight structure that can easily adapt to the emergence of an official API. Therefore, I strongly discourage using it for any other purposes. If you have access to official PaLM-2 API, replace the provided response with the corresponding official code.
    Downloads: 0 This Week
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  • 3
    SSD in PyTorch 1.0

    SSD in PyTorch 1.0

    High quality, fast, modular reference implementation of SSD in PyTorch

    ...Multi-GPU training and inference: We use DistributedDataParallel, you can train or test with arbitrary GPU(s), the training schema will change accordingly. Add your own modules without pain. We abstract backbone, Detector, BoxHead, BoxPredictor, etc. You can replace every component with your own code without changing the code base. For example, You can add EfficientNet as the backbone, just add efficient_net.py (ALREADY ADDED) and register it, specific it in the config file, It's done! Smooth and enjoyable training procedure: we save the state of model, optimizer, scheduler, training iter, you can stop your training and resume training exactly from the save point without change your training CMD.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Petals

    Petals

    Run 100B+ language models at home, BitTorrent-style

    ...You get the comforts of an API with the flexibility of PyTorch. You can also host BLOOMZ, a version of BLOOM fine-tuned to follow human instructions in the zero-shot regime — just replace bloom-petals with bloomz-petals. Petals runs large language models like BLOOM-176B collaboratively — you load a small part of the model, then team up with people serving the other parts to run inference or fine-tuning.
    Downloads: 2 This Week
    Last Update:
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