Showing 7 open source projects for "apache framework"

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  • 1
    SentenceTransformers

    SentenceTransformers

    Multilingual sentence & image embeddings with BERT

    SentenceTransformers is a Python framework for state-of-the-art sentence, text and image embeddings. The initial work is described in our paper Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. You can use this framework to compute sentence / text embeddings for more than 100 languages. These embeddings can then be compared e.g. with cosine-similarity to find sentences with a similar meaning. This can be useful for semantic textual similar, semantic search, or paraphrase...
    Downloads: 2 This Week
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  • 2
    PaddleNLP

    PaddleNLP

    Easy-to-use and powerful NLP library with Awesome model zoo

    PaddleNLP It is a natural language processing development library for flying paddles, with Easy-to-use text area API, Examples of applications for multiple scenarios, and High-performance distributed training Three major features, aimed at improving the modeling efficiency of the flying oar developer's text field, aiming to improve the developer's development efficiency in the text field, and provide rich examples of NLP applications. Provide rich industry-level pre-task capabilities...
    Downloads: 2 This Week
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  • 3
    Haystack

    Haystack

    Haystack is an open source NLP framework to interact with your data

    Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning,...
    Downloads: 5 This Week
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  • 4
    langchain-prefect

    langchain-prefect

    Tools for using Langchain with Prefect

    Large Language Models (LLMs) are interesting and useful  -  building apps that use them responsibly feels like a no-brainer. Tools like Langchain make it easier to build apps using LLMs. We need to know details about how our apps work, even when we want to use tools with convenient abstractions that may obfuscate those details. Prefect is built to help data people build, run, and observe event-driven workflows wherever they want. It provides a framework for creating deployments on a whole...
    Downloads: 0 This Week
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  • 5
    MMGeneration

    MMGeneration

    MMGeneration is a powerful toolkit for generative models

    MMGeneration has been merged in MMEditing. And we have supported new-generation tasks and models. MMGeneration is a powerful toolkit for generative models, especially for GANs now. It is based on PyTorch and MMCV. The master branch works with PyTorch 1.5+. We currently support training on Unconditional GANs, Internal GANs, and Image Translation Models. Support for conditional models will come soon. A plentiful toolkit containing multiple applications in GANs is provided to users. GAN...
    Downloads: 0 This Week
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  • 6
    GPT-NeoX

    GPT-NeoX

    Implementation of model parallel autoregressive transformers on GPUs

    This repository records EleutherAI's library for training large-scale language models on GPUs. Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training. For those looking for a TPU-centric codebase, we...
    Downloads: 0 This Week
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  • 7
    TFKit

    TFKit

    Handling multiple nlp task in one pipeline

    TFKit is a tool kit mainly for language generation. It leverages the use of transformers on many tasks with different models in this all-in-one framework. All you need is a little change of config. You can use tfkit for model training and evaluation with tfkit-train and tfkit-eval. The key to combine different task together is to make different task with same data format. All data will be in csv format - tfkit will use csv for all task, normally it will have two columns, first columns is the...
    Downloads: 0 This Week
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