Search Results for "mime decoder encoder" - Page 6
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Showing 132 open source projects for "mime decoder encoder"
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An All in One encoder/decoder for the masses Current version: 1.0 Supports: Base64, Hex, URL, URL+, Rot13 (Caesar), MD5, SHA-1, String Reverse, VBScript/JScript Encoder/decoder, ASCII convert
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Coconut Data Framework
Define data structure and data objects for Cocoa applications
Coconut Data Framework defines data structure and data objects for Cocoa application. Each data has encoder/decoder to/from XML representations -
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libuformat
libuformat is ANSI-C library to implement micro-format
libuformat is ANSI-C library to implement micro-format. It defines data structure for micro-format and encoder, decoder for it. -
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A portable C library of common data types and algorithms (such as linked lists, dynamic arrays, binary trees, stacks and queues, base64 encoder/decoder, MD5). Efficient, stable, fast, secure and extremely well documented.
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t5-base
Flexible text-to-text transformer model for multilingual NLP tasks
t5-base is a pre-trained transformer model from Google’s T5 (Text-To-Text Transfer Transformer) family that reframes all NLP tasks into a unified text-to-text format. With 220 million parameters, it can handle a wide range of tasks, including translation, summarization, question answering, and classification. Unlike traditional models like BERT, which output class labels or spans, T5 always generates text outputs. It was trained on the C4 dataset, along with a variety of supervised NLP... -
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bart-large-cnn
Summarization model fine-tuned on CNN/DailyMail articles
facebook/bart-large-cnn is a large-scale sequence-to-sequence transformer model developed by Meta AI and fine-tuned specifically for abstractive text summarization. It uses the BART architecture, which combines a bidirectional encoder (like BERT) with an autoregressive decoder (like GPT). Pre-trained on corrupted text reconstruction, the model was further trained on the CNN/DailyMail dataset—a collection of news articles paired with human-written summaries. It performs particularly well in generating concise, coherent, and human-readable summaries from longer texts. ...