pinferencia
Python + Inference - Model Deployment library in Python. Simplest model inference server ever. (by underneathall)
pyro
Deep universal probabilistic programming with Python and PyTorch (by pyro-ppl)
| pinferencia | pyro | |
|---|---|---|
| 21 | 9 | |
| 556 | 8,364 | |
| 0.0% | 0.5% | |
| 0.0 | 8.4 | |
| about 1 year ago | 10 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pinferencia
Posts with mentions or reviews of pinferencia.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-27.
- Show HN: Pinferencia, Deploy Your AI Models with Pretty UI and REST API
-
Stop Writing Flask to Serve/Deploy Your Model: Pinferencia is Here
Go visit: Pinferencia (underneathall.app) for detailed examples.
- Looking for a reference design pattern for an image to image microservice
-
Google T5 Translation as a Service with Just 7 lines of Codes
**Pinferencia** makes it super easy to serve any model with just three extra lines.
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Pre-trained Model with Fine Tuning/Transfer Learning or Design and Train from Scratch?
Hi, recently I'm writing some tutorials involving HuggingFace's models for my project Pinferencia.
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[D] Pre-trained Model with Fine Tuning/Transfer Learning or Design and Train from Scratch?
Hi, I'm the creator of Pinferencia, recently I'm writer some tutorial involving HuggingFace's models.
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GPT2 — Text Generation Transformer: How to Use & How to Serve
If you haven't heard of Pinferencia go to its github page or its homepage to check it out, it's an amazing library help you deploy your model with ease.
-
My first Udemy course on ML Ops deployment!
Please allow me to recommend another simple but serious deployment tools which is also compatible with triton, torchserve, kubeflow, tf serving: Pinferencia
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Easiest Way to Deploy HuggingFace Transformers
Never heard of Pinferencia? It’s not late. Go to its GitHub to take a look. Don’t forget to give it a star if you like it.
-
what is the easiest way to deploy a nlp model?
Check this out https://github.com/underneathall/pinferencia
pyro
Posts with mentions or reviews of pyro.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-11.
-
Show HN: Designing Bridges with PyTorch
Mostly I use pytorch for statistical modeling https://pyro.ai . Under the hood that package uses a lot of Monte Carlo integration and variational methods (i.e. integration by optimization). It does support neural nets, but probably >80% of pyro users stick to simpler hierarchical Bayesian models.
- Pyro: The Universal, Probablistic Programming Language
- The Jupyter+Git problem is now solved
- Pyro: Deep universal probabilistic programming with Python and PyTorch
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Computational Bayesian Inference Techniques
Amortized Variational Inference (Like done in pyro.ai with neural networks)
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[P] torchegranate: a PyTorch rewrite of the pomegranate library for probabilistic modeling
Can you compare this to Pyro, which is also built on top of PyTorch?
- [Q] Updated book or review paper on MCMC methods
- Is anyone here working in uncertainty estimation in neural networks?
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[D] Do you train and deploy models using just one framework or multiple frameworks at work?
Using pyod, statmodels, scikit-learn, Tensorflow and pyro.ai (that is using PyTorch as backend). I always use the same framework for training and for production.
What are some alternatives?
When comparing pinferencia and pyro you can also consider the following projects:
server - The Triton Inference Server provides an optimized cloud and edge inferencing solution.
PyMC - Bayesian Modeling and Probabilistic Programming in Python
budgetml - Deploy a ML inference service on a budget in less than 10 lines of code.
scikit-learn - scikit-learn: machine learning in Python
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
llmware - Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.
trueskill - An implementation of the TrueSkill rating system for Python
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
probability - Probabilistic reasoning and statistical analysis in TensorFlow
serving - A flexible, high-performance serving system for machine learning models
Keras - Deep Learning for humans