andreagemelli
Follow
Lists (1)
Stars
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
DomainBed is a suite to test domain generalization algorithms
An awesome list of layout generation papers
A Gradio web UI for Large Language Models.
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gan…
🦜🔗 Build context-aware reasoning applications
The simplest, fastest repository for training/finetuning medium-sized GPTs.
DocEnTr: An end-to-end document image enhancement transformer - ICPR 2022
[ICDAR 2023] (Oral) An End-to-End Unified Domain Adaptive Transformer for Document Instance Segmentation
😎 Awesome list of tools and projects with the awesome LangChain framework
QLoRA: Efficient Finetuning of Quantized LLMs
A curated list of resources for Document Understanding (DU) topic
PyTorch implementation of "LayoutTransformer: Layout Generation and Completion with Self-attention" to appear in ICCV 2021
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
Official PyTorch implementation of our paper "Multimodal Tree Decoder for Table of Contents Extraction in Document Images"
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Camoscio: An Italian instruction-tuned language model based on LLaMA
WebGL + Three.js implementation of Kenny Mitchell's post-processing algorithm for volumetric light scattering rendering.
Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)
🔥Highlighting the top ML papers every week.
Public repo for DeepLearning.AI MLEP Specialization
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data