Search Results for "scripts"
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Showing 72 open source projects for "scripts"
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1
Stable Diffusion Version 2
High-Resolution Image Synthesis with Latent Diffusion Models
...The repository provides code for training and running Stable Diffusion-style models, instructions for installing dependencies (with notes about performance libraries like xformers), and guidance on hardware/driver requirements for efficient GPU inference and training. It’s organized as a practical, developer-focused toolkit: model code, scripts for inference, and examples for using memory-efficient attention and related optimizations are included so researchers and engineers can run or adapt the model for their own projects. The project sits within a larger ecosystem of Stability AI repositories (including inference-only reference implementations like SD3.5 and web UI projects) and the README points users toward compatible components, recommended CUDA/PyTorch versions. -
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Code World Model (CWM)
Research code artifacts for Code World Model (CWM)
...It is explicitly trained on execution traces, action-observation trajectories, and agentic interactions in controlled environments. It has been developed to better capture how code, actions, and state interact over time. The repository provides inference code, reproducibility scripts, prompt guides, and more. It has model cards, utilities, demos, and evaluation artifacts. Inference scripts and utilities for code generation tasks. Evaluation benchmarks on code, mathematics, and reasoning tasks. Demos, serving code, and evaluation pipelines. -
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DeepSeek-OCR 2
Visual Causal Flow
...It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents with rich spatial structure. The repository provides model code and inference scripts that let researchers and developers run and benchmark the system on both images and PDFs, with support for batch evaluation and optimized pipelines leveraging vLLM and transformers. -
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DeepSeek-OCR
Contexts Optical Compression
DeepSeek-OCR is an open-source optical character recognition solution built as part of the broader DeepSeek AI vision-language ecosystem. It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body... -
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Qwen3-TTS
Qwen3-TTS is an open-source series of TTS models
...It provides researchers and developers with tools to transform text into expressive, intelligible audio, supporting multiple languages and voice characteristics tuned for clarity and fluidity. The project includes pre-trained models and inference scripts that let users synthesize speech locally or integrate TTS into larger pipelines such as voice assistants, accessibility tools, or multimedia generation workflows. Because it’s part of the broader Qwen ecosystem, it benefits from the model’s understanding of linguistic nuances, enabling more accurate pronunciation, prosody, and contextual delivery than many traditional TTS systems. ... -
6
DreamCraft3D
Official implementation of DreamCraft3D
...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 post-processing modules (e.g. mesh smoothing, texturing) to make the outputs more output-ready. Because 3D generation is hardware‐intensive, the repository likely also includes optimizations like quantization, pruning, or inference accelerations (e.g. using FlashMLA or DeepEP) to make the generation pipeline faster or more efficient. ... -
7
FLUX.1
Official inference repo for FLUX.1 models
...The project is part of a larger family of FLUX models developed by Black Forest Labs, designed to produce high-quality, detailed visuals from text descriptions with competitive prompt adherence and artistic fidelity. This repo focuses on running the open-source model variants efficiently, providing scripts, model loading logic, and examples for local installations, and supports integration with Python toolchains like PyTorch and popular generative pipelines. Users can launch CLI tools to generate images, experiment with different FLUX variants, and extend the base code for research-oriented applications. -
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CLIP
CLIP, Predict the most relevant text snippet given an image
...Once trained, you can give it any text labels and ask it to pick which label best matches a given image—even without explicit training for that classification task. The repository provides code for model architecture, preprocessing transforms, evaluation pipelines, and example inference scripts. Because it generalizes to arbitrary labels via text prompts, CLIP is a powerful tool for tasks that involve interpreting images in terms of descriptive language. -
9
Ling
Ling is a MoE LLM provided and open-sourced by InclusionAI
...The project offers different sizes (Ling-lite, Ling-plus) and emphasizes flexibility and efficiency: being able to scale, adapt expert activation, and perform across a range of natural language/reasoning tasks. Example scripts, inference pipelines, and documentation. The codebase includes inference, examples, models, documentation, and model download infrastructure. As more developers and researchers engage with the platform, we can expect rapid advancements and improvements, leading to even more sophisticated applications. Model inference and API code (e.g. integration with Transformers). ... -
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10
HunyuanVideo-I2V
A Customizable Image-to-Video Model based on HunyuanVideo
...It extends video generation so that given a static reference image plus an optional prompt, it generates a video sequence that preserves the reference image’s identity (especially in the first frame) and allows stylized effects via LoRA adapters. The repository includes pretrained weights, inference and sampling scripts, training code for LoRA effects, and support for parallel inference via xDiT. Resolution, video length, stability mode, flow shift, seed, CPU offload etc. Parallel inference support using xDiT for multi-GPU speedups. LoRA training / fine-tuning support to add special effects or customize generation. -
11
DINOv3
Reference PyTorch implementation and models for DINOv3
DINOv3 is the third-generation iteration of Meta’s self-supervised visual representation learning framework, building upon the ideas from DINO and DINOv2. It continues the paradigm of learning strong image representations without labels using teacher–student distillation, but introduces a simplified and more scalable training recipe that performs well across datasets and architectures. DINOv3 removes the need for complex augmentations or momentum encoders, streamlining the pipeline while... -
12
DFlash
Block Diffusion for Ultra-Fast Speculative Decoding
...This approach has been shown to deliver lossless acceleration on models like Qwen3-8B by combining block diffusion techniques with efficient batching, making it ideal for applications where latency and cost matter. The project includes support for multiple draft models, example integration code, and scripts to benchmark performance, and it is structured to work with popular model serving stacks like SGLang and the Hugging Face Transformers ecosystem. -
13
InstantCharacter
Personalize Any Characters with a Scalable Diffusion Transformer
InstantCharacter is a tuning-free diffusion transformer framework created by Tencent Hunyuan / InstantX team, which enables generating images of a specific character (subject) from a single reference image, preserving identity and character features. Uses adapters, so full fine-tuning of the base model is not required. Demo scripts and pipeline API (via infer_demo.py, pipeline.py) included. It works by adapting a base image generation model with a lightweight adapter so that you can produce character-preserving generations in various downstream tasks (e.g. changing pose, clothing, scene) without needing full model fine-tuning. Works with huggingface/transformers/diffusers ecosystems. -
14
FramePack
Lets make video diffusion practical
FramePack explores compact representations for sequences of image frames, targeting tasks where many near-duplicate frames carry redundant information. The idea is to “pack” frames by detecting shared structure and storing differences efficiently, which can accelerate training or inference on video-like data. By reducing I/O and memory bandwidth, datasets become lighter to load while models still see the essential temporal variation. The repository demonstrates both packing and unpacking... -
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DeepSeek Coder
DeepSeek Coder: Let the Code Write Itself
DeepSeek-Coder is a series of code-specialized language models designed to generate, complete, and infill code (and mixed code + natural language) with high fluency in both English and Chinese. The models are trained from scratch on a massive corpus (~2 trillion tokens), of which about 87% is code and 13% is natural language. This dataset covers project-level code structure (not just line-by-line snippets), using a large context window (e.g. 16K) and a secondary fill-in-the-blank objective... -
16
Vidi2
Large Multimodal Models for Video Understanding and Editing
...Vidi targets applications like intelligent video editing, automated video search, content analysis, and editing assistance, enabling users to efficiently locate relevant segments and objects in hours-long footage. The system is built with open-source release in mind, giving developers access to model code, inference scripts, and evaluation pipelines so they can reproduce research results or integrate Vidi into their own video-processing workflows. -
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HunyuanImage-3.0
A Powerful Native Multimodal Model for Image Generation
...The model is intended to be competitive with closed-source image generation systems, aiming for high fidelity, prompt adherence, fine detail, and even “world knowledge” reasoning (i.e. leveraging context, semantics, or common sense in generation). The GitHub repo includes code, scripts, model loading instructions, inference utilities, prompt handling, and integration with standard ML tooling (e.g. Hugging Face / Transformers). -
18
SAM 3D Body
Code for running inference with the SAM 3D Body Model 3DB
...The model is trained to be robust in diverse, in-the-wild conditions, so it handles varied clothing, viewpoints, and backgrounds while maintaining strong accuracy across multiple human-pose benchmarks. The repository provides Python code to run inference, utilities to download checkpoints from Hugging Face, and demo scripts that turn images into 3D meshes and visualizations. There are Jupyter notebooks that walk you through setting up the model, running it on example images, and visualizing outputs in 3D, making it approachable even if you are not a 3D expert. -
19
Claude Code SDK Python
Python SDK for Claude Agent
...The SDK includes core client classes, asynchronous query functions, and support for custom tools and hooks within Claude sessions. It is designed to integrate with local Python workflows and allow developers to embed Claude Code capabilities directly in their applications or scripts. The repo is MIT-licensed and includes documentation and installation instructions (requires Python 3.10+, Node installation of Claude Code). Example usage shows how to stream responses, parse structured message blocks, or create persistent client sessions. -
20
Tongyi DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
...It uses a mix of synthetic data generation, fine-tuning and reinforcement learning; supports benchmarks like web search, document understanding, question answering, “agentic” tasks; provides inference tools, evaluation scripts, and “web agent” style interfaces. The aim is to enable more autonomous, agentic models that can perform sustained knowledge gathering, reasoning, and synthesis across multiple modalities (web, files, etc.). -
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HunyuanVideo-Foley
Multimodal Diffusion with Representation Alignment
HunyuanVideo-Foley is a multimodal diffusion model from Tencent Hunyuan for high-fidelity Foley (sound effects) audio generation synchronized to video scenes. It is designed to generate audio that matches both visual content and textual semantic cues, for use in video production, film, advertising, games, etc. The model architecture aligns audio, video, and text representations to produce realistic synchronized soundtracks. Produces high-quality 48 kHz audio output suitable for professional... -
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HY-Motion 1.0
HY-Motion model for 3D character animation generation
HY-Motion 1.0 is an open-source, large-scale AI model suite developed by Tencent’s Hunyuan team that generates high-quality 3D human motion from simple text prompts, enabling the automatic production of fluid, diverse, and semantically accurate animations without manual keyframing or rigging. Built on advanced deep learning architectures that combine Diffusion Transformer (DiT) and flow matching techniques, HY-Motion scales these approaches to the billion-parameter level, resulting in strong... -
23
Flow Matching
A PyTorch library for implementing flow matching algorithms
flow_matching is a PyTorch library implementing flow matching algorithms in both continuous and discrete settings, enabling generative modeling via matching vector fields rather than diffusion. The underlying idea is to parameterize a flow (a time-dependent vector field) that transports samples from a simple base distribution to a target distribution, and train via matching of flows without requiring score estimation or noisy corruption—this can lead to more efficient or stable generative... -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
DINOv2 is a self-supervised vision learning framework that produces strong, general-purpose image representations without using human labels. It builds on the DINO idea of student–teacher distillation and adapts it to modern Vision Transformer backbones with a carefully tuned recipe for data augmentation, optimization, and multi-crop training. The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval,... -
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GLM-4
GLM-4 series: Open Multilingual Multimodal Chat LMs
GLM-4 is a family of open models from ZhipuAI that spans base, chat, and reasoning variants at both 32B and 9B scales, with long-context support and practical local-deployment options. The GLM-4-32B-0414 models are trained on ~15T high-quality data (including substantial synthetic reasoning data), then post-trained with preference alignment, rejection sampling, and reinforcement learning to improve instruction following, coding, function calling, and agent-style behaviors. The...
