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Decision brief
Pinferencia is a Python library that simplifies the process of setting up model inference servers with minimal code.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (1262d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- 160 low (160 low)
- As of 1mo
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Install
pip install pinferenciaSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Pinferencia is designed to deploy machine learning and deep learning models with minimal code.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Jul 31, 2026
- Languages
- python
Source: github.language+pyproject.toml · Jul 31, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 31, 2026)
```python title="app.py"Source link
Tags
README
Quick Start
Serve Any Model
from pinferencia import Server
class MyModel:
def predict(self, data):
return sum(data)
model = MyModel()
service = Server()
service.register(model_name="mymodel", model=model, entrypoint="predict")
Just run:
pinfer app:service
Hooray, your service is alive. Go to http://127.0.0.1:8501/ and have fun.
Any Deep Learning Models? Just as easy. Simple train or load your model, and register it with the service. Go alive immediately.
Hugging Face
Details: HuggingFace Pipeline - Vision
from transformers import pipeline
from pinferencia import Server
vision_classifier = pipeline(task="image-classification")
def predict(data):
return vision_classifier(images=data)
service = Server()
service.register(model_name="vision", model=predict)
Pytorch
import torch
from pinferencia import Server
For agents
This page has a .md twin and JSON over the API.