Instructions to use flair/ner-german-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use flair/ner-german-large with Flair:
from flair.data import Sentence from flair.models import SequenceTagger tagger = SequenceTagger.load("flair/ner-german-large") sentence = Sentence("George Washington went to Washington.") tagger.predict(sentence) print(sentence) - Notebooks
- Google Colab
- Kaggle
Download loss.tsv from flair/ner-german-large: direct link, hf CLI and curl.
- Browser
- Download file 857 Bytes
-
https://huggingface.co/flair/ner-german-large/resolve/main/loss.tsv
- Command line
-
hf download hf://flair/ner-german-large/loss.tsv
-
curl -L -o loss.tsv https://huggingface.co/flair/ner-german-large/resolve/main/loss.tsv
857 Bytes
| EPOCH TIMESTAMP BAD_EPOCHS LEARNING_RATE TRAIN_LOSS | |
| 1 16:51:59 4 0.0000 0.2866137816264941 | |
| 2 17:16:36 4 0.0000 0.19963635197194995 | |
| 3 17:41:09 4 0.0000 0.19381841593759824 | |
| 4 18:05:44 4 0.0000 0.16904323373543453 | |
| 5 18:30:18 4 0.0000 0.17083178105798114 | |
| 6 18:54:35 4 0.0000 0.16211920515636655 | |
| 7 19:18:47 4 0.0000 0.16189787430929792 | |
| 8 19:42:57 4 0.0000 0.15914436206804433 | |
| 9 20:07:08 4 0.0000 0.1469039810866205 | |
| 10 20:31:16 4 0.0000 0.1492166711907655 | |
| 11 20:55:24 4 0.0000 0.15147419168516288 | |
| 12 21:19:32 4 0.0000 0.13647247537528812 | |
| 13 21:43:54 4 0.0000 0.14614263093116467 | |
| 14 22:08:30 4 0.0000 0.13674926033805127 | |
| 15 22:33:01 4 0.0000 0.1387276056972103 | |
| 16 22:57:29 4 0.0000 0.13758350506155864 | |
| 17 23:21:41 4 0.0000 0.13729583443464166 | |
| 18 23:45:55 4 0.0000 0.13997356167795372 | |
| 19 00:10:06 4 0.0000 0.13157929521994233 | |
| 20 00:34:21 4 0.0000 0.1353108691912222 |