Showing 4 open source projects for "sstp-client"

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    Python Client For NLP Cloud

    Python Client For NLP Cloud

    NLP Cloud serves high performance pre-trained or custom models for NER

    NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search,...
    Downloads: 0 This Week
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  • 2
    Basaran

    Basaran

    Basaran, an open-source alternative to the OpenAI text completion API

    ...Detokenizer that handles surrogates and whitespace. Multi-GPU support with optional 8-bit quantization. Real-time partial progress using server-sent events. Compatible with OpenAI API and client libraries. Comes with a fancy web-based playground. Docker images are available on Docker Hub and GitHub Packages.
    Downloads: 0 This Week
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  • 3
    commit-autosuggestions

    commit-autosuggestions

    A tool that AI automatically recommends commit messages

    ...However, most code changes are not made only by add of the code, and some parts of the code are deleted. We plan to slowly conquer languages that are not currently supported. To run this project, you need a flask-based inference server (GPU) and a client (commit module). If you don't have a GPU, don't worry, you can use it through Google Colab.
    Downloads: 0 This Week
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  • 4
    gpt2-client

    gpt2-client

    Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.

    ...The model has 4 versions - 124M, 345M, 774M, and 1558M - that differ in terms of the amount of training data fed to it and the number of parameters they contain. Finally, gpt2-client is a wrapper around the original gpt-2 repository that features the same functionality but with more accessiblity, comprehensibility, and utilty. You can play around with all four GPT-2 models in less than five lines of code. Install client via pip. The generation options are highly flexible. You can mix and match based on what kind of text you need generated, be it multiple chunks or one at a time with prompts.
    Downloads: 1 This Week
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