Dimitre Oliveira's starred repositories
parler-tts
Inference and training library for high-quality TTS models.
awesome-osml-for-devs
List of resources, libraries and more for developers who would like to build with open-source machine learning off-the-shelf
llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
dreambooth-keras
Implementation of DreamBooth in KerasCV and TensorFlow.
keras-sd-serving
showing various ways to serve Keras based stable diffusion
semantic-segmentation-ml-pipeline
Machine Learning Pipeline for Semantic Segmentation with TensorFlow Extended (TFX) and various GCP products
deploy-hf-tf-vision-models
This repository shows various ways of deploying a vision model (TensorFlow) from 🤗 Transformers.
sentence-transformers
Multilingual Sentence & Image Embeddings with BERT
awesome-mlops
A curated list of references for MLOps
image_search_with_natural_language
Application for searching images from natural language queries
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Made-With-ML
Learn how to design, develop, deploy and iterate on production-grade ML applications.
AI-Expert-Roadmap
Roadmap to becoming an Artificial Intelligence Expert in 2022
mlops-course
Learn how to design, develop, deploy and iterate on production-grade ML applications.
awesome-graph-classification
A collection of important graph embedding, classification and representation learning papers with implementations.
awesome-rl
Reinforcement learning resources curated
BERT-related-papers
BERT-related papers
AI_Curriculum
Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.
awesome-papers
Papers & presentation materials from Hugging Face's internal science day
Production-Level-Deep-Learning
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.