Download manifests/0f/github.com__graylab__picap.json from OpenScientificCodeRegistry/Database: direct link, hf CLI and curl.
- Browser
- Download file 4.12 kB
-
https://huggingface.co/datasets/OpenScientificCodeRegistry/Database/resolve/main/manifests/0f/github.com__graylab__picap.json
- Command line
-
hf download hf://datasets/OpenScientificCodeRegistry/Database/manifests/0f/github.com__graylab__picap.json
-
curl -L -o github.com__graylab__picap.json https://huggingface.co/datasets/OpenScientificCodeRegistry/Database/resolve/main/manifests/0f/github.com__graylab__picap.json
4.12 kB
| { | |
| "format": "oscr-script-manifest/1", | |
| "repository": "github.com/graylab/picap", | |
| "url": "https://github.com/Graylab/picap", | |
| "host": "github.com", | |
| "commit": "a8c81c239cb9e63cbcc3f301500dff25168b4554", | |
| "license": "MIT", | |
| "license_confirmed_by": "license file LICENSE", | |
| "redistribution": "yes", | |
| "files": [ | |
| { | |
| "path": ".ipynb_checkpoints/notebook_predict_directory-checkpoint.ipynb", | |
| "sha256": "a4e8df11a83349edb937c97750bcd2fde7ef1ac35f01de6d51f47154b29295ff", | |
| "language": "Jupyter", | |
| "lines": 51, | |
| "truncated": false, | |
| "block": 5, | |
| "row": 16089 | |
| }, | |
| { | |
| "path": ".ipynb_checkpoints/sample_notebook-checkpoint.ipynb", | |
| "sha256": "25dcdc0a4c84c37cc735f9fb002838a1a09ca913a54a23943cf9030f88d118c1", | |
| "language": "Jupyter", | |
| "lines": 103, | |
| "truncated": false, | |
| "block": 5, | |
| "row": 16270 | |
| }, | |
| { | |
| "path": "LICENSE", | |
| "sha256": "9c16d93cf112afee200b64e365967dc043458a7f24a987390d52769d4de2fedf", | |
| "language": "License", | |
| "lines": 21, | |
| "truncated": false, | |
| "block": 6, | |
| "row": 1407 | |
| }, | |
| { | |
| "path": "README.md", | |
| "sha256": "d53336f4b946abb366699247927123ffc91d1bd3c48964fcde3008e766bf7f47", | |
| "language": "Text", | |
| "lines": 117, | |
| "truncated": false, | |
| "block": 8, | |
| "row": 10359 | |
| }, | |
| { | |
| "path": "egnn/.ipynb_checkpoints/egnn-checkpoint.py", | |
| "sha256": "1a58e6829aa76af5894f3cfab781fa833c22f3b99623fffe7e82807a192050f8", | |
| "language": "Python", | |
| "lines": 455, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 8299 | |
| }, | |
| { | |
| "path": "egnn/ae.py", | |
| "sha256": "1b0c9fd8a498e88f27b3f731b59af38c40c2d6d0af6e547f0f8e4148f4c73686", | |
| "language": "Python", | |
| "lines": 168, | |
| "truncated": false, | |
| "block": 6, | |
| "row": 43740 | |
| }, | |
| { | |
| "path": "egnn/egnn.py", | |
| "sha256": "9addf476084f1977dee849c79e5bd38feb320ba6c7b1371c253908bd1600f51f", | |
| "language": "Python", | |
| "lines": 480, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 8202 | |
| }, | |
| { | |
| "path": "egnn/gcl.py", | |
| "sha256": "05c956dab2c8d4a7e3d7297aa0325629f1077cb8d1d2b1074206f98497a97575", | |
| "language": "Python", | |
| "lines": 351, | |
| "truncated": false, | |
| "block": 1, | |
| "row": 8862 | |
| }, | |
| { | |
| "path": "notebook_predict_directory.ipynb", | |
| "sha256": "a4e8df11a83349edb937c97750bcd2fde7ef1ac35f01de6d51f47154b29295ff", | |
| "language": "Jupyter", | |
| "lines": 51, | |
| "truncated": false, | |
| "block": 5, | |
| "row": 16089 | |
| }, | |
| { | |
| "path": "preprocess.py", | |
| "sha256": "02afac647ecc0d7259d821ac57e0fc2b3f1d8fb28be0d5ceecdfaf5221476de0", | |
| "language": "Python", | |
| "lines": 635, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 7728 | |
| }, | |
| { | |
| "path": "run_both.py", | |
| "sha256": "6b6eecd1a121d4da2ce786d292bc3c984226214d52fccff6828906f3c79f22a3", | |
| "language": "Python", | |
| "lines": 504, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 6847 | |
| }, | |
| { | |
| "path": "sample_notebook.ipynb", | |
| "sha256": "25dcdc0a4c84c37cc735f9fb002838a1a09ca913a54a23943cf9030f88d118c1", | |
| "language": "Jupyter", | |
| "lines": 103, | |
| "truncated": false, | |
| "block": 5, | |
| "row": 16270 | |
| }, | |
| { | |
| "path": "training_code/train_1.py", | |
| "sha256": "5aa141832cfe229291bd3e85f46c8278aaf626c57ec68b888c1191b8c1edb03b", | |
| "language": "Python", | |
| "lines": 131, | |
| "truncated": false, | |
| "block": 6, | |
| "row": 40255 | |
| }, | |
| { | |
| "path": "training_code/train_2-carb.py", | |
| "sha256": "9d80cc7483bcf3ad1f8df0575d12ddc5b464a2efc075a3149ff8b140ae4894df", | |
| "language": "Python", | |
| "lines": 137, | |
| "truncated": false, | |
| "block": 6, | |
| "row": 39344 | |
| }, | |
| { | |
| "path": "training_code/train_2-prot.py", | |
| "sha256": "779f82d793f04d8864708c31c076aa0545baed2d87525b57ee9ea1d5c254d9af", | |
| "language": "Python", | |
| "lines": 165, | |
| "truncated": false, | |
| "block": 6, | |
| "row": 41735 | |
| }, | |
| { | |
| "path": "training_code/utils_model.py", | |
| "sha256": "2f3407d87aaab096ab22a6835d8f00f9cd94332a250200d5d18127633e9e6962", | |
| "language": "Python", | |
| "lines": 266, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 659 | |
| }, | |
| { | |
| "path": "utils.py", | |
| "sha256": "40e9ddf7f19a398d5ad3921db8844d291a1cdb048f1d56bdf58e22cf8954602d", | |
| "language": "Python", | |
| "lines": 783, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 9793 | |
| } | |
| ] | |
| } |