Instructions to use Jsevisal/balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jsevisal/balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Jsevisal/balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Jsevisal/balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch") model = AutoModelForTokenClassification.from_pretrained("Jsevisal/balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
21e95dd
-
Update README.md
e653728 -
update model card README.md
9470355 -
Training complete
f905e9b -
Training in progress, epoch 20
7fbb1ac -
Training in progress, epoch 17
54549fe -
Training in progress, epoch 14
89dc84d -
Training in progress, epoch 11
7ba7af4 -
Training in progress, epoch 8
af56e99 -
Training in progress, epoch 5
9de6870 -
Training in progress, epoch 1
b4b73c9 -
Training in progress, epoch 14
bf1cd89 -
Training in progress, epoch 2
98e9425 -
Training in progress, epoch 1
6b98d2f -
Training in progress, epoch 13
c3f428a -
Training in progress, epoch 1
9e8085c -
Training in progress, epoch 14
216cd71 -
Training in progress, epoch 1
957af89 -
initial commit
4b60aff