Showing 2 open source projects for "multi"

View related business solutions
  • Veeam Data Platform v13.1 - Get Your Free Trial Icon
    Veeam Data Platform v13.1 - Get Your Free Trial

    Secure by design, portable by default. Recover clean, fast, anywhere. Start a free trial.

    Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
    Try it Free
  • Go from Code to Production URL in Seconds Icon
    Go from Code to Production URL in Seconds

    Cloud Run deploys apps in any language instantly. Scales to zero. Pay only when code runs.

    Skip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
    Start Free
  • 1
    NVIDIA NeMo

    NVIDIA NeMo

    Toolkit for conversational AI

    ...Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI architectures are typically large and require a lot of data and compute for training. NeMo uses PyTorch Lightning for easy and performant multi-GPU/multi-node mixed-precision training. Supported models: Jasper, QuartzNet, CitriNet, Conformer-CTC, Conformer-Transducer, Squeezeformer-CTC, Squeezeformer-Transducer, ContextNet, LSTM-Transducer (RNNT), LSTM-CTC. NGC collection of pre-trained speech processing models.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2
    NLP.js

    NLP.js

    An NLP library for building bots

    ...Search the best substring of a string with less Levenshtein distance to a given pattern. Get stemmers and tokenizers for several languages. Sentiment Analysis for phrases (with negation support). Named Entity Recognition and management, multi-language support, and acceptance of similar strings, so the introduced text does not need to be exact. Natural Language Processing Classifier, to classify an utterance into intents. NLP Manager, a tool able to manage several languages, the Named Entities for each language, the utterances, and intents for the training of the classifier, and for a given utterance return the entity extraction, the intent classification and the sentiment analysis.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next