There are 4 repositories under bentoml topic.
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
Pybind11 bindings for Whisper.cpp
All the available resources to master MLOPS from scratch
A simple web application that lets you replace any part of an image with an image generated based on your description.
This repository contains instructions, template source code and examples on how to serve/deploy machine learning models using various frameworks and applications such as Docker, Flask, FastAPI, BentoML, Streamlit, MLflow and even code on how to deploy your machine learning model as an android app.
Analyzes your GitHub Profile and presents you with a report on how likely you are to become the next MLH Fellow!
A bentoML-powered API to transcribe audio and make sense of it
A simple yet complete guide to MLOps tools and practices - from a conventional way to a modern approach of working with ML projects.
My repo for the Machine Learning Engineering bootcamp 2022 by DataTalks.Club
MLOps Implementing "Brain Computer Interface" on Kubernetes
Generate novel text - novel finetuned from skt KoGPT2 base v2 - 한국어
API serving for your diffusers models
Miscellaneous codes and writings for MLOps
Helm Chart for installing Yatai on Kubernetes ⎈
Deploying machine learning model using 10+ different deployment tools
A pipeline built on MetaFlow for training Fashion MNIST dataset using Pytorch, experiment tracking using MLFlow and model deployment using BentoML
Machine Learning Web Application. Helps to visualize a character-by-character breakdown of how sentiment analysis classifies text
To automatically tag people in various chat groups
Flask-ML grants any type of user (not only data scientist) an easy and compact UI Tool that supports BentoML to process images based on state-of-the-art machine learning approaches.
Upload an image and find similar images easily!
Contains my experiments made with the mighty library BentoML
A pipeline built on ZenML for training digit MNIST dataset using Pytorch, experiment tracking using MLFlow and model deployment using BentoML
My practices in mlops tools 🥵. Feel free to explore the various scripts and files ⚙️. I am just diving into the world of production-ready Machine Learning with streamlined workflows. 🤖
Testing deployment of PyMC models using MLFlow and BentoML.
Python bentoML(API serving for machine learning model) example & tutorial code
Serve Llama 3.3 70B (with AWQ quantization) using vLLM and deploy it on BentoCloud.