Instructions to use dcarpintero/fastai-interstellar-object with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use dcarpintero/fastai-interstellar-object with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("dcarpintero/fastai-interstellar-object") - Notebooks
- Google Colab
- Kaggle
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Download README.md from dcarpintero/fastai-interstellar-object: direct link, hf CLI and curl.
- Browser
- Download file 1.42 kB
-
https://huggingface.co/dcarpintero/fastai-interstellar-object/resolve/4f801afe51f429dbc8c60e26b134d680ce7d16a9/README.md
- Command line
-
hf download hf://dcarpintero/fastai-interstellar-object@4f801afe51f429dbc8c60e26b134d680ce7d16a9/README.md
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curl -L -o README.md https://huggingface.co/dcarpintero/fastai-interstellar-object/resolve/4f801afe51f429dbc8c60e26b134d680ce7d16a9/README.md
1.42 kB
metadata
license: apache-2.0
metrics:
- accuracy
pipeline_tag: image-classification
tags:
- fastai
- astronomy
Interstellar Classifier
Classify images of interstellar objects such as galaxies, nebulae, comets, asteroids, quasars, and star clusters.
Built for the fast.ai Practical Deep Learning Course by:
- creating a custom dataset (less than 150 images per label) using Bing search API;
- augmenting the dataset; and,
- fine tuning ResNet50 (1 + 3 epochs) in paperspace.com.
Try at: https://huggingface.co/spaces/dcarpintero/fastai-interstellar
Two versions of the model are provided:
Object Model
This version fastai-interstellar-object
Recognizes a (limited) set of specific interstellar objects:
m31 andromedam33 triangulumm81 bodem82 cigarngc 1300m104 sombrerom51 whirlpoolm42 orion nebulam17 omega nebulam45 pleiades star cluster
Accuracy: 94.1%
Class Model
Available at fastai-interstellar-class
Classifies an image under an astronomy class:
asteroidcometgalaxynebulaeplanetquasar in spacestar cluster
Accuracy: 84%