Search Results for "assembly source code" - Page 32

Showing 2494 open source projects for "assembly source code"

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  • 1
    DreamCraft3D

    DreamCraft3D

    Official implementation of DreamCraft3D

    DreamCraft3D is DeepSeek’s generative 3D modeling framework / model family that likely extends their earlier 3D efforts (e.g. Shap-E or Point-E style models) with more capability, control, or expression. The name suggests a “dream crafting” metaphor—users probably supply textual or image prompts and generate 3D assets (point clouds, meshes, scenes). The repository includes model code, inference scripts, sample prompts, and possibly dataset preparation pipelines. It may integrate rendering or...
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  • 2
    Smallpond

    Smallpond

    A lightweight data processing framework built on DuckDB and 3FS

    smallpond is a lightweight distributed data processing framework built by DeepSeek, designed to scale DuckDB workloads over clusters using their 3FS (Fire-Flyer File System) backend. The idea is to preserve DuckDB’s fast analytics engine but lift it from single-node to multi-node settings, giving you the ability to operate on large datasets (e.g. petabyte scale) without moving to a heavyweight system like Spark. Users write Python-like code (via DataFrame APIs or SQL strings) to express...
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  • 3
    Tiktoken

    Tiktoken

    tiktoken is a fast BPE tokeniser for use with OpenAI's models

    tiktoken is a high-performance, tokenizer library (based on byte-pair encoding, BPE) designed for use with OpenAI’s models. It handles encoding and decoding text to token IDs efficiently, with minimal overhead. Because tokenization is a fundamental step in preparing text for models, tiktoken is optimized for speed, memory, and correctness in model contexts (e.g. matching OpenAI’s internal tokenization). The repo supports multiple encodings (e.g. “cl100k_base”) and lets users switch encoding...
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  • 4
    Instructor

    Instructor

    Structured outputs for llms

    Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. Its customizable nature permits the definition of...
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  • 5
    Kubeflow pipelines

    Kubeflow pipelines

    Machine Learning Pipelines for Kubeflow

    Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. A pipeline is a description of an ML workflow, including all of the components in the workflow and how they combine in the form of a graph. The pipeline includes the definition of the inputs (parameters) required to run the pipeline and the inputs and outputs of each component. A pipeline component is a self-contained set of user code, packaged as...
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  • 6
    Cobbler

    Cobbler

    Cobbler is a versatile Linux deployment server

    Cobbler is a Linux installation server that allows for rapid setup of network installation environments. It glues together and automates many associated Linux tasks so you do not have to hop between many various commands and applications when deploying new systems, and, in some cases, changing existing ones. Cobbler can help with provisioning, managing DNS and DHCP, package updates, power management, configuration management orchestration, and much more. Automation is the key to speed,...
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  • 7
    PML

    PML

    The easiest way to use deep metric learning in your application

    This library contains 9 modules, each of which can be used independently within your existing codebase, or combined together for a complete train/test workflow. To compute the loss in your training loop, pass in the embeddings computed by your model, and the corresponding labels. The embeddings should have size (N, embedding_size), and the labels should have size (N), where N is the batch size. The TripletMarginLoss computes all possible triplets within the batch, based on the labels you...
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  • 8
    PyG

    PyG

    Graph Neural Network Library for PyTorch

    PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,...
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  • 9
    Ansible Molecule

    Ansible Molecule

    Molecule aids in the development and testing of Ansible roles

    Molecule project is designed to aid in the development and testing of Ansible roles. Molecule provides support for testing with multiple instances, operating systems and distributions, virtualization providers, test frameworks and testing scenarios. Molecule encourages an approach that results in consistently developed roles that are well-written, easily understood and maintained. Molecule supports only the latest two major versions of Ansible (N/N-1), meaning that if the latest version is...
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  • 10
    TensorFlow Model Garden

    TensorFlow Model Garden

    Models and examples built with TensorFlow

    The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models...
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  • 11
    Eel

    Eel

    A Python library for making simple Electron-like HTML/JS GUI apps

    Eel is a little Python library for making simple Electron-like offline HTML/JS GUI apps, with full access to Python capabilities and libraries. Eel hosts a local webserver, then lets you annotate functions in Python so that they can be called from Javascript, and vice versa. Eel is designed to take the hassle out of writing short and simple GUI applications. If you are familiar with Python and web development, probably just jump to this example which picks random file names out of the given...
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  • 12
    TensorBoardX

    TensorBoardX

    tensorboard for pytorch (and chainer, mxnet, numpy, etc.)

    The SummaryWriter class provides a high-level API to create an event file in a given directory and add summaries and events to it. The class updates the file contents asynchronously. This allows a training program to call methods to add data to the file directly from the training loop, without slowing down training. TensorboardX now supports logging directly to Comet. Comet is a free cloud based solution that allows you to automatically track, compare and explain your experiments. It adds a...
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  • 13
    Data Version Control

    Data Version Control

    Git-based data version control for machine learning workflows

    ...DVC also provides a pipeline system that defines the stages of machine learning workflows, making experiments reproducible and easier to manage. By tracking dependencies between code, data, and parameters, the system ensures that only the necessary stages are re-run when changes occur. DVC also includes experiment tracking capabilities that allow users to compare different training runs.
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  • 14
    EasyR1

    EasyR1

    An Efficient, Scalable, Multi-Modality RL Training Framework

    ...The framework is also organized to help you compare training strategies (e.g., pure SFT vs. preference optimization) so you can see what actually moves metrics in math, code, and multi-step reasoning. For teams exploring open reasoning models, EasyR1 provides an opinionated yet flexible path from dataset to deployable checkpoints.
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  • 15
    SageMaker Hugging Face Inference Toolkit

    SageMaker Hugging Face Inference Toolkit

    Library for serving Transformers models on Amazon SageMaker

    SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging...
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  • 16
    DreamO

    DreamO

    A Unified Framework for Image Customization

    DreamO is a unified, open-source framework from ByteDance for advanced image customization and generation that consolidates multiple “image manipulation” tasks into a single system, rather than requiring separate specialized models. Built on a diffusion-transformer (DiT) backbone, it supports a diverse set of tasks — including identity preservation, virtual “try-on” (e.g. clothing, accessories), style transfer, IP adaptation (objects/characters), and layout/condition-aware customizations —...
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  • 17
    InfiniteYou

    InfiniteYou

    Flexible Photo Recrafting While Preserving Your Identity

    InfiniteYou is an open-source image-generation and “identity-preserving image editing / generation” framework from ByteDance, designed to generate high-fidelity images that preserve a subject’s identity while allowing flexible editing or re-creation according to textual prompts. Using an architecture built around diffusion transformers (DiTs), InfiniteYou introduces a component called InfuseNet that injects identity features derived from reference images into the generation process — via...
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  • 18
    OWL

    OWL

    Optimized Workforce Learning for General Multi-Agent Assistance

    OWL (Optimized Workforce Learning) is a sophisticated open-source framework built on the CAMEL-AI ecosystem for orchestrating teams of AI agents to collaboratively solve complex, real-world tasks with dynamic planning and automation capabilities. Unlike single-agent systems, it treats task completion as a collaborative workforce where agents take on specialized roles (planning, execution, analysis) and coordinate via a modular multi-agent architecture that supports flexible teamwork across...
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  • 19
    1D Visual Tokenization and Generation

    1D Visual Tokenization and Generation

    This repo contains the code for 1D tokenizer and generator

    The 1D Visual Tokenization and Generation project from ByteDance introduces a novel “one-dimensional” tokenizer designed for images: instead of representing images with large grids of 2D tokens (as in many prior generative/image-modeling systems), it compresses images into as few as 32 discrete tokens (or more, optionally) — thereby achieving a very compact, efficient representation that drastically speeds up generation and reconstruction while retaining strong fidelity. This compact...
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  • 20
    UNO

    UNO

    A Universal Customization Method for Single and Multi Conditioning

    UNO is a project by ByteDance introduced in 2025, titled “A Universal Customization Method for Both Single and Multi-Subject Conditioning.” It suggests a framework for image (or more general generative) modeling where the model can be conditioned either on a single subject or multiple subjects — which may correspond to generating or customizing images featuring specific people, styles, or objects, possibly with fine-grained control over subject identity or composition. Because the project is...
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  • 21
    Optopsy

    Optopsy

    A nimble options backtesting library for Python

    Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. Optopsy is a small simple library that offloads...
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  • 22
    BackAnt CLI

    BackAnt CLI

    Let your AI agent create clean, easy to maintain flask backends

    BackAnt CLI is an AI-native backend scaffolding tool designed to generate production-ready Flask APIs from a JSON specification or a small set of CLI commands. Its main goal is to reduce the repetitive work involved in setting up layered backend projects by generating key application components automatically rather than forcing developers to assemble them by hand. The tool creates a structured backend architecture that includes routes, services, repositories, models, startup files, Docker...
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  • 23
    Top Deep Learning Projects

    Top Deep Learning Projects

    A list of popular github projects related to deep learning

    TopDeepLearning is a curated index of the most popular GitHub projects related to deep learning, ranked by their star count. Rather than being a library itself, it serves as a curated roadmap and reference guide for anyone exploring the deep learning ecosystem — from beginners to experienced practitioners. By aggregating high-star projects across frameworks (TensorFlow, PyTorch), tools (computer vision, NLP, reinforcement learning), tutorials, and research code, it helps users quickly...
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  • 24
    AWS SDK for pandas

    AWS SDK for pandas

    Easy integration with Athena, Glue, Redshift, Timestream, Neptune

    aws-sdk-pandas (formerly AWS Data Wrangler) bridges pandas with the AWS analytics stack so DataFrames flow seamlessly to and from cloud services. With a few lines of code, you can read from and write to Amazon S3 in Parquet/CSV/JSON/ORC, register tables in the AWS Glue Data Catalog, and query with Amazon Athena directly into pandas. The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling...
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  • 25
    TextFSM

    TextFSM

    Python module for parsing semi-structured text into python tables

    TextFSM is a Python library created by Google that provides a template-based state machine engine for parsing semi-structured text. It is particularly useful for extracting structured data from command-line interface (CLI) outputs, such as those from network devices, routers, and switches. By defining parsing logic through reusable template files, TextFSM transforms unstructured text into structured data like lists or tables without requiring complex regular expression code. Each template...
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