Search Results for "decoder"
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Showing 307 open source projects for "decoder"
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Pytorch-toolbelt
PyTorch extensions for fast R&D prototyping and Kaggle farming
...Extras for Catalyst library (Visualization of batch predictions, additional metrics). By design, both encoder and decoder produces a list of tensors, from fine (high-resolution, indexed 0) to coarse (low-resolution) feature maps. Access to all intermediate feature maps is beneficial if you want to apply deep supervision losses on them or encoder-decoder of object detection task. -
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simplejson
simplejson is a simple, fast, extensible JSON encoder/decoder
simplejson is a simple, fast, complete, correct and extensible JSON <http://json.org> encoder and decoder for Python 3.3+ with legacy support for Python 2.5+. It is pure Python code with no dependencies but includes an optional C extension for a serious speed boost. simplejson is the externally maintained development version of the json library included with Python (since 2.6). This version is tested with the latest Python 3.8 and maintains backward compatibility with Python 3.3+ and the legacy Python 2.5 - Python 2.7 releases. ... -
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UltraJSON
Ultra fast JSON decoder and encoder written in C with Python bindings
UltraJSON is an ultra-fast JSON encoder and decoder written in pure C with bindings for Python 3.7+. May be used as a drop-in replacement for most other JSON parsers for Python. Used to enable special encoding of "unsafe" HTML characters into safer Unicode sequences. Limits output to ASCII and escapes all extended characters above 127. Default is True. If your end format supports UTF-8, setting this option to false is highly recommended to save space. -
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Zstandard
Zstandard - Fast real-time compression algorithm
...It also offers a special mode for small data, called dictionary compression. The reference library offers a very wide range of speed / compression trade-off, and is backed by an extremely fast decoder (see benchmarks below). Zstandard library is provided as open source software using a BSD license. Its format is stable and published as IETF RFC 8478. The negative compression levels, specified with --fast=#, offer faster compression and decompression speed in exchange for some loss in compression ratio compared to level 1, as seen in the table above. ... -
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go-json
Fast JSON encoder/decoder compatible with encoding/json for Go
Fast JSON encoder/decoder compatible with encoding/json for Go. -
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Pilipala
Recommendations, live streams, video playback
PiliPala is a GPL‑licensed, Flutter-built third-party Bilibili client that works on Android, iOS, desktop, and web. It includes recommendations, live streams, video playback with gestures, adjustable playback speed, AV quality and decoder controls, bullet comments, subtitles, snapshots, fullscreen modes, UI theming, blacklists, and more. -
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Solidity
The Smart Contract Programming Language
Solidity is a statically-typed curly-braces programming language designed for developing smart contracts that run on Ethereum. Solidity 0.8.4 adds custom structured errors, allows more flexible configuration of the SMTChecker and fixes a bug in the Solidity ABI decoder v2. Read more about the bug here. With v0.8.4, errors can be defined inside and outside of contracts (including interfaces and libraries). This provides a convenient and gas-efficient way to explain to users why an operation failed. As a relatively young language, Solidity is advancing at a rapid speed. We aim for a regular (non-breaking) release every 2-3 weeks, with approximately two breaking releases per year. ... -
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Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
...A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. These tasks are jointly represented as a sequence of tokens to be predicted by the decoder, allowing a single model to replace many stages of a traditional speech-processing pipeline. The multitask training format uses a set of special tokens that serve as task specifiers or classification targets. -
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nghttp2
HTTP/2 C Library and tools
...Since then we have updated nghttp2 library constantly to the latest specification and nghttp2 is now one of the most mature HTTP/2 implementations. HTTP/2 utilizes header compression method called HPACK. We offer HPACK encoder and decoder are available as public API. nghttp2 library itself is a bit low-level. The experimental high-level C++ API is also available. We have Python binding of this library, but we have not covered everything yet. -
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Segment Anything
Provides code for running inference with the SegmentAnything Model
...It’s a promptable segmenter: you guide it with points, boxes, or rough masks, and it predicts high-quality object masks consistent with the prompt. The architecture separates a powerful image encoder from a lightweight mask decoder, so the heavy vision work can be computed once and the interactive part stays fast. A bundled automatic mask generator can sweep an image and propose many object masks, which is useful for dataset bootstrapping or bulk annotation. The repository includes ready-to-use weights, Python APIs, and example notebooks demonstrating both interactive and automatic modes. ... -
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Generic Image Decoder
A standalone, portable generic Ada package for decoding images
The Generic Image Decoder is a package for decoding a broad variety of image formats, from any data stream, to any kind of medium. Unconditionally portable code: OS-, CPU-, compiler- independent code. More information on... http://gen-img-dec.sf.net Alire crate: https://alire.ada.dev/crates/gid Mirror: https://github.com/zertovitch/gid -
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Granite Code Models
A Family of Open Foundation Models for Code Intelligence
Granite Code Models are IBM’s open-source, decoder-only models tailored for code tasks such as fixing bugs, explaining and documenting code, and modernizing codebases. Trained on code from 116 programming languages, the family targets strong performance across diverse benchmarks while remaining accessible to the community. The repository introduces the model lineup, intended uses, and evaluation highlights, and it complements IBM’s broader Granite initiative spanning multiple modalities. ... -
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Typia
Super-fast/easy runtime validations and serializations
Super-fast/easy runtime validations and serializations through transformation. -
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far2l
Linux port of FAR v2
Linux fork of FAR Manager v2. Works also on OSX/MacOS and BSD (but the latter is not tested on a regular manner). Plug-ins that are currently working: NetRocks (SFTP/SCP/FTP/FTPS/SMB/NFS/WebDAV), colorer, multiarc, tmppanel, align, autowrap, drawing, edit case, SimpleIndent, Calculator, Python (optional scripting support). -
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Step1X-Edit
A SOTA open-source image editing model
Step1X-Edit is a state-of-the-art open-source image editing model/framework that uses a multimodal large language model (LLM) together with a diffusion-based image decoder to let users edit images simply via natural-language instructions plus a reference image. You supply an existing image and a textual command — e.g. “add a ruby pendant on the girl’s neck” or “make the background a sunset over mountains” — and the model interprets the instruction, computes a latent embedding combining the image content and user intent, then decodes a new image implementing the edit. ... -
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x-transformers
A simple but complete full-attention transformer
A simple but complete full-attention transformer with a set of promising experimental features from various papers. Proposes adding learned memory key/values prior to attending. They were able to remove feedforwards altogether and attain a similar performance to the original transformers. I have found that keeping the feedforwards and adding the memory key/values leads to even better performance. Proposes adding learned tokens, akin to CLS tokens, named memory tokens, that is passed through... -
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Step3-VL-10B
Multimodal model achieving SOTA performance
...It achieves this efficiency and strong performance through unified pre-training on a massive 1.2 trillion-token multimodal corpus that jointly optimizes a language-aligned perception encoder with a powerful decoder, creating deep synergy between image processing and text understanding. -
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go-toml
Go library for the TOML file format
...As much as possible, this library is designed to behave similarly as the standard library's encoding/json. While go-toml favors usability, it is written with performance in mind. Most operations should not be shockingly slow. Decoder can be set to "strict mode", which makes it error when some parts of the TOML document was not present in the target structure. This is a great way to check for typos. When most decoding errors occur, go-toml returns DecodeError), which contains a human readable contextualized version of the error. TOML supports native local date/times. ... -
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GLM-OCR
Accurate × Fast × Comprehensive
GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B), enabling deployment in high-concurrency services and edge environments. ... -
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CTranslate2
Fast inference engine for Transformer models
CTranslate2 is a C++ and Python library for efficient inference with Transformer models. The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU. The execution is significantly faster and requires less resources than general-purpose deep learning frameworks on supported models and tasks thanks to many... -
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TorchAudio
Data manipulation and transformation for audio signal processing
The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch... -
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LLM Foundry
LLM training code for MosaicML foundation models
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy... -
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Bard API
The unofficial python package that returns response of Google Bard
The Python package returns a response of Google Bard through the value of the cookie. This package is designed for application to the Python package ExceptNotifier and Co-Coder. Please note that the bardapi is not a free service, but rather a tool provided to assist developers with testing certain functionalities due to the delayed development and release of Google Bard's API. It has been designed with a lightweight structure that can easily adapt to the emergence of an official API.... -
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AV1 AVIF
AV1 Image File Format Specification - ISO-BMFF/HEIF derivative
AV1 AVIF is the official specification and reference design for the AV1 Image File Format (AVIF), defining how AV1-encoded bitstreams are packaged into the HEIF container format (based on ISOBMFF) to produce AVIF files. The project outlines the syntax and semantics required for AVIF compliance, including support for multiple image profiles, color depths, chroma subsampling modes, HDR/WCG, alpha channels, animation/image sequences, and various color-space/bit-depth combinations — making AVIF... -
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FireRedASR
Open-source industrial-grade ASR models
...The project includes multiple model variants to meet different application needs, such as high-accuracy end-to-end interaction using an encoder-adapter-LLM framework and efficient real-time recognition using attention-based encoder-decoder architectures, giving developers flexibility in balancing performance and resource constraints. FireRedASR not only excels in traditional speech recognition tasks but also demonstrates strong capability in challenging scenarios like singing lyrics recognition, where accurate transcription is often difficult for conventional models.
