pascal-maker

pascal-maker's Stars

• CompVis/stable-diffusion

  A latent text-to-image diffusion model

  Language:Jupyter Notebook68.9k56371710.2k

• meta-llama/llama-recipes

  Scripts for fine-tuning Meta Llama with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supporting a number of candid inference solutions such as HF TGI, VLLM for local or cloud deployment. Demo apps to showcase Meta Llama for WhatsApp & Messenger.

  Language:Jupyter Notebook15.7k2043972.3k

• IDEA-Research/Grounded-Segment-Anything

  Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

  Language:Jupyter Notebook15.5k1153951.4k

• BlinkDL/RWKV-LM

  RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

  Language:Python12.9k132224874

• NielsRogge/Transformers-Tutorials

  This repository contains demos I made with the Transformers library by HuggingFace.

  Language:Jupyter Notebook9.7k1434541.5k

• karpathy/minbpe

  Minimal, clean code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.

  Language:Python9.3k8538875

• UX-Decoder/Segment-Everything-Everywhere-All-At-Once

  [NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"

  Language:Python4.4k59149412

• argmaxinc/WhisperKit

  On-device Speech Recognition for Apple Silicon

  Language:Swift4.1k39158343

• Marker-Inc-Korea/AutoRAG

  AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation

  Language:Python3k23580229

• huggingface/datatrove

  Freeing data processing from scripting madness by providing a set of platform-agnostic customizable pipeline processing blocks.

  Language:Python2.1k47137157

• dora-rs/dora

  DORA (Dataflow-Oriented Robotic Architecture) is middleware designed to streamline and simplify the creation of AI-based robotic applications. It offers low latency, composable, and distributed dataflow capabilities. Applications are modeled as directed graphs, also referred to as pipelines.

  Language:Rust1.6k3014198

• huggingface/nanotron

  Minimalistic large language model 3D-parallelism training

  Language:Python1.3k4393135

• Renumics/spotlight

  Interactively explore unstructured datasets from your dataframe.

  Language:TypeScript1.1k199383

• SuperMedIntel/Medical-SAM-Adapter

  Adapting Segment Anything Model for Medical Image Segmentation

  Language:Python1k1010091

• GetStream/stream-chat-flutter

  Flutter Chat SDK - Build your own chat app experience using Dart, Flutter and the Stream Chat Messaging API.

  Language:Dart95023917347

• GetStream/stream-chat-swift

  💬 iOS Chat SDK in Swift - Build your own app chat experience for iOS using the official Stream Chat API

  Language:Swift86849656210

• IDEA-Research/OpenSeeD

  [ICCV 2023] Official implementation of the paper "A Simple Framework for Open-Vocabulary Segmentation and Detection"

  Language:Python673223943

• NVlabs/EmerNeRF

  PyTorch Implementation of EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision

  Language:Python582273045

• uni-medical/SAM-Med3D

  SAM-Med3D: An Efficient General-purpose Promptable Segmentation Model for 3D Volumetric Medical Image

  Language:Python54568674

• chungmin99/garfield

  [CVPR'24] Group Anything with Radiance Fields

  Language:Python40083231

• ml-explore/mlx-data

  Efficient framework-agnostic data loading

  Language:C++386142742

• preternatural-explore/mlx-swift-chat

  A multi-platform SwiftUI frontend for running local LLMs with Apple's MLX framework.

  Language:Swift36714722

• noahfarr/rlx

  A reinforcement learning framework based on MLX.

  Language:Python2215118

• Aradhye2002/EcoDepth

  [CVPR'2024] Official implementation of the paper "ECoDepth: Effective Conditioning of Diffusion Models for Monocular Depth Estimation"

  Language:Jupyter Notebook17351715

• computervisioneng/face-attendance-system

  Language:Python162412106

• fcjian/PromptDet

  PromptDet: Towards Open-vocabulary Detection using Uncurated Images, ECCV2022

  Language:Python1622167

• Shengcao-Cao/HASSOD

  [NeurIPS 2023] HASSOD: Hierarchical Adaptive Self-Supervised Object Detection

  Language:Python52233

• SHAHFAISAL80/Crowd-localization-and-counting

  Accurately locating each head's position in the crowd scenes is a crucial task in the field of crowd analysis. However, traditional density-based methods only predict coarse prediction, and segmentation/detection-based methods cannot handle extremely dense scenes and large-range scale-variations crowds.

  Language:Python20206

• Tony-Luna/100-Days-Of-Computer-Vision

  100 days challenge of reading and implementing computer vision concepts using popular python libraries like OpenCV and Keras.

  Language:Python18303

• koyeb/example-llamaindex-rag

  Language:EJS8302