Some useful Pytorch models, circa 2025

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  • License: MIT License (MIT)
  • Author: Nicholas Bailey
  • Requires: Python >=3.8
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Project description

broccoli

Some useful PyTorch models, circa 2025.

broccoli

Getting started

You can install broccoli with

pip install broccoli-ml

PyTorch is a peer dependency of broccoli, which means

  • You will need to make sure you have PyTorch installed in order to use broccoli
  • PyTorch will not be installed automatically when you install broccoli

We take this approach because PyTorch versioning is environment-specific and we don't know where you will want to use broccoli. If we automatically install PyTorch for you, there's a good chance we would get it wrong!

Therefore, please also make sure you install PyTorch.

Usage examples

...

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for nicholasbailey from gravatar.com nicholasbailey

Unverified details

These details have not been verified by PyPI
Meta
  • License: MIT License (MIT)
  • Author: Nicholas Bailey
  • Requires: Python >=3.8
Classifiers

Release history Release notifications | RSS feed

This version

30.1.0

30.0.0

29.3.0

29.2.0

29.1.0

29.0.0

28.0.0

27.1.1

27.1.0

27.0.0

26.2.0

26.1.0

26.0.0

25.0.0

24.0.1

24.0.0

23.1.0

23.0.3

23.0.2

23.0.1

23.0.0

22.1.0

22.0.2

22.0.1

22.0.0

21.0.1

21.0.0

20.1.0

20.0.0

19.7.1

19.7.0

19.6.0

19.5.0

19.4.0

19.3.0

19.1.3

19.1.2

19.1.1

19.1.0

19.0.0

18.4.0

18.3.0

18.2.0

18.1.0

18.0.0

17.3.0

17.2.0

17.1.0

17.0.0

16.1.0

16.0.4

16.0.3

16.0.2

16.0.1

16.0.0

15.12.0

15.10.4

15.10.2

15.10.1

15.10.0

15.9.0

15.8.1

15.8.0

15.7.1

15.7.0

15.6.0

15.5.0

15.4.2

15.4.1

15.4.0

15.3.0

15.2.0

15.1.0

15.0.1

15.0.0

14.0.1

14.0.0

13.0.6

13.0.5

13.0.4

13.0.3

13.0.2

13.0.1

13.0.0

12.3.1

12.3.0

12.2.0

12.1.0

12.0.0

11.0.0

10.2.0

10.1.1

10.1.0

10.0.1

10.0.0

9.7.0

9.6.0

9.5.1

9.5.0

9.4.2

9.4.1

9.4.0

9.3.0

9.2.2

9.2.1

9.2.0

9.1.0

9.0.0

7.0.0

6.0.1

6.0.0

5.2.0

5.1.4

5.1.3

5.1.2

5.1.1

5.1.0

5.0.0

4.0.1

4.0.0

3.3.1

3.3.0

3.2.0

3.1.3

3.1.2

3.1.1

3.1.0

3.0.1

3.0.0

2.0.0

1.3.0

1.2.3

1.2.2

1.2.1

1.2.0

1.1.0

1.0.0

0.40.0

0.39.0

0.38.0

0.37.0

0.36.0

0.35.1

0.35.0

0.34.0

0.33.2

0.33.1

0.33.0

0.32.0

0.31.2

0.31.1

0.31.0

0.30.0

0.29.1

0.29.0

0.28.0

0.27.0

0.26.0

0.25.0

0.24.3

0.24.2

0.24.1

0.24.0

0.23.1

0.23.0

0.22.0

0.21.1

0.21.0

0.20.0

0.19.0

0.18.1

0.18.0

0.17.0

0.16.0

0.15.2

0.15.1

0.15.0

0.14.1

0.14.0

0.13.6

0.13.5

0.13.4

0.13.3

0.13.2

0.13.1

0.13.0

0.12.0

0.11.0

0.10.0

0.9.0

0.8.1

0.8.0

0.7.0

0.6.0

0.5.5

0.5.4

0.5.3

0.5.2

0.5.1

0.5.0

0.4.4

0.4.3

0.4.2

0.4.1

0.4.0

0.3.0

0.2.0

0.1.41

0.1.40

0.1.39

0.1.38

0.1.37

0.1.36

0.1.35

0.1.34

0.1.33

0.1.32

0.1.31

0.1.30

0.1.29

0.1.28

0.1.27

0.1.26

0.1.25

0.1.24

0.1.23

0.1.22

0.1.21

0.1.20

0.1.19

0.1.18

0.1.17

0.1.16

0.1.15

0.1.14

0.1.13

0.1.12

0.1.11

0.1.10

0.1.9

0.1.8

0.1.7

0.1.6

0.1.5

0.1.4

0.1.3

0.1.2

0.1.1

0.1.0

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