Download manifests/1e/github.com__chenebuah__q-catnet.json from OpenScientificCodeRegistry/Database: direct link, hf CLI and curl.
- Browser
- Download file 2.14 kB
-
https://huggingface.co/datasets/OpenScientificCodeRegistry/Database/resolve/main/manifests/1e/github.com__chenebuah__q-catnet.json
- Command line
-
hf download hf://datasets/OpenScientificCodeRegistry/Database/manifests/1e/github.com__chenebuah__q-catnet.json
-
curl -L -o github.com__chenebuah__q-catnet.json https://huggingface.co/datasets/OpenScientificCodeRegistry/Database/resolve/main/manifests/1e/github.com__chenebuah__q-catnet.json
2.14 kB
| { | |
| "format": "oscr-script-manifest/1", | |
| "repository": "github.com/chenebuah/q-catnet", | |
| "url": "https://github.com/chenebuah/Q-CatNet", | |
| "host": "github.com", | |
| "commit": "ccb7406080e3df9efc31c82574c2e152e73d3f12", | |
| "license": "MIT", | |
| "license_confirmed_by": "license file LICENSE", | |
| "redistribution": "yes", | |
| "files": [ | |
| { | |
| "path": "Descriptor.py", | |
| "sha256": "1f362c41f1441b7eb7c6e61a9ac74a358ae2355d5fbd0954396fa79bc07d92f0", | |
| "language": "Python", | |
| "lines": 554, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 10557 | |
| }, | |
| { | |
| "path": "LICENSE", | |
| "sha256": "f10cfb0112ce42eb2fadb5f06381f0b50c462479d71c1a72ca4ad2b9b02871f1", | |
| "language": "License", | |
| "lines": 21, | |
| "truncated": false, | |
| "block": 6, | |
| "row": 1741 | |
| }, | |
| { | |
| "path": "Learning_Model.py", | |
| "sha256": "b8ae72662f151d6e87ec999b6c02611b7e3ee76489c78e0244fcbdc7fef5cd9e", | |
| "language": "Python", | |
| "lines": 155, | |
| "truncated": false, | |
| "block": 6, | |
| "row": 45214 | |
| }, | |
| { | |
| "path": "README.md", | |
| "sha256": "da84a0ad77543ef1c0491aeab9f24bb7d1e1dec37e6f76483f41e94cbddafeba", | |
| "language": "Text", | |
| "lines": 1, | |
| "truncated": false, | |
| "block": 8, | |
| "row": 9447 | |
| }, | |
| { | |
| "path": "equivariant_baselines/dimenetpp_baseline.py", | |
| "sha256": "9d4a501d29fa43a0a8366c2977e0dea33c03c85b1856867a2a4f2b842af3a4df", | |
| "language": "Python", | |
| "lines": 537, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 8440 | |
| }, | |
| { | |
| "path": "equivariant_baselines/equiformerv2_baseline.py", | |
| "sha256": "9c628ba8e3cd292ac2809778ab475972eb2c25b5c07af253d0e67765b114f84d", | |
| "language": "Python", | |
| "lines": 386, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 6089 | |
| }, | |
| { | |
| "path": "equivariant_baselines/gemnet_t_baseline.py", | |
| "sha256": "85e3036913b286d8adf77ed49e19662ae353898fd946cf8bae71354ebbe6aa1d", | |
| "language": "Python", | |
| "lines": 306, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 4117 | |
| }, | |
| { | |
| "path": "equivariant_baselines/mace_baseline.py", | |
| "sha256": "89410d27eb9873a48ef047eff177b768fa9caaa94f45682375217c6885a545a1", | |
| "language": "Python", | |
| "lines": 393, | |
| "truncated": false, | |
| "block": 7, | |
| "row": 6133 | |
| } | |
| ] | |
| } |