Showing 7 open source projects for "mod-apache-snmp"

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  • 1
    Regex

    Regex

    Generate matching and non matching strings based on regex patterns

    Generate matching and non-matching strings. This is a java library that, given a regex pattern, allows to generation of matching strings. Iterate through unique matching strings. Generate not matching strings. Follow the link to Online IDE with created project: JDoodle. Enter your pattern and see the results. By design a+, a* and a{n,} patterns in regex imply an infinite number of characters should be matched. When generating data, that would mean values of infinite length might be...
    Downloads: 3 This Week
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  • 2
    TextGen

    TextGen

    textgen, Text Generation models

    Implementation of Text Generation models. textgen implements a variety of text generation models, including UDA, GPT2, Seq2Seq, BART, T5, SongNet and other models, out of the box. UDA, non-core word replacement. EDA, simple data augmentation technique: similar words, synonym replacement, random word insertion, deletion, replacement. This project refers to Google's UDA (non-core word replacement) algorithm and EDA algorithm, based on TF-IDF to replace some unimportant words in sentences with...
    Downloads: 2 This Week
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  • 3
    Intelligent Java

    Intelligent Java

    Integrate with the latest language models, image generation and speech

    Intelligent java (IntelliJava) is the ultimate tool to integrate with the latest language models and deep learning frameworks using java. The library provides an intuitive functions for sending input to models like ChatGPT and DALL·E, and receiving generated text, speech or images. With just a few lines of code, you can easily access the power of cutting-edge AI models to enhance your projects. Access ChatGPT, GPT3 to generate text and DALL·E to generate images. OpenAI is preferred for...
    Downloads: 0 This Week
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  • 4
    Texar-PyTorch

    Texar-PyTorch

    Integrating the Best of TF into PyTorch, for Machine Learning

    Texar-PyTorch is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar-PyTorch was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror...
    Downloads: 0 This Week
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  • 5
    onnxt5

    onnxt5

    Summarization, translation, sentiment-analysis, text-generation, etc.

    Summarization, translation, sentiment analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in the alpha stage, therefore some functionalities such as beam searches are still in development. The simplest way to get started for generation is to use the default pre-trained version of T5 on ONNX included in the package. Please note that the first time you call get_encoder_decoder_tokenizer, the models are being downloaded which might...
    Downloads: 0 This Week
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  • 6
    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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  • 7
    GPT2 for Multiple Languages

    GPT2 for Multiple Languages

    GPT2 for Multiple Languages, including pretrained models

    With just 2 clicks (not including Colab auth process), the 1.5B pretrained Chinese model demo is ready to go. The contents in this repository are for academic research purpose, and we do not provide any conclusive remarks. Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC) Simplifed GPT2 train scripts(based on Grover, supporting TPUs). Ported bert tokenizer, multilingual corpus compatible. 1.5B GPT2 pretrained Chinese model (~15G corpus, 10w steps)....
    Downloads: 2 This Week
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