{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Loads and runs computer vision models from Roboflow or local sources using PyTorch, ONNX, TensorRT, or Hugging Face backends, with a unified API across different model architectures.","skillfed_tags":["computer-vision","model-inference","roboflow-integration"],"use_cases":["Load and run a pretrained Roboflow model (e.g., RFDetr) on images without writing backend-specific code.","Deploy a custom model trained on Roboflow platform in production by loading it with an API key.","Run local custom model implementations from a directory for production deployment of non-standard architectures.","Chain inference with supervision to visualize predictions (bounding boxes, masks, etc.) on images.","Switch between inference backends (PyTorch to TensorRT, for example) without changing application code."],"what_it_does":"inference-models is a unified inference library for running computer vision models trained on Roboflow or built locally. It abstracts away backend selection (PyTorch, ONNX, TensorRT, Hugging Face) and model loading, letting you call a single API regardless of the underlying architecture\u2014whether you're running object detection, segmentation, OCR, or vision-language tasks. The library includes pretrained models (RFDetr, SAM, Florence, DocTR, EasyOCR, YOLO, and others) and supports custom models from the Roboflow platform via API key, as well as local model implementations.\n\nThe package is designed for production use and integrates with supervision for annotation and post-processing. It requires Python 3.10\u20133.12 and pulls in 44 runtime dependencies including numpy, torch, torchvision, transformers, and diffusers, making it best suited for environments with adequate compute and storage. The library reached its first stable release at version 0.19.0 and is actively maintained, though the API may still evolve.","worth_installing":"Yes, if you are building computer vision applications on Roboflow models or need a unified inference API across multiple backends and model types. The heavy dependency footprint and Python version cap (3.10\u20133.12) make it unsuitable for lightweight or resource-constrained environments. License treatment is unclear\u2014verify model-specific restrictions before production deployment. No known vulnerabilities as of the query date."},"id":"inference-models","links":{"html":"https://skillfed.io/packages/inference-models","md":"https://skillfed.io/packages/inference-models.md","pypi":"https://pypi.org/project/inference-models/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-14","license_spdx":null,"license_treatment":"unclear","name":"inference-models","python_support":"capped_below_current","summary":"The new inference engine for Computer Vision models"},"popularity":{"monthly_downloads":93972,"position":13353,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.35.2"}