Instructions to use numblilbug/multilabel-rubert-sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use numblilbug/multilabel-rubert-sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="numblilbug/multilabel-rubert-sentiment-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("numblilbug/multilabel-rubert-sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("numblilbug/multilabel-rubert-sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, epoch 1
b967c82 -
Training in progress, epoch 1
146de41 -
Training in progress, epoch 1
5aa66ef -
Training in progress, epoch 10
c677067 -
Training in progress, epoch 6
d448069 -
Training in progress, epoch 1
663ba28 -
Training in progress, epoch 1
0247d7d -
Training in progress, epoch 1
7f392c6 -
Training in progress, epoch 1
a3fef11 -
Training in progress, epoch 1
536d853 -
Training in progress, epoch 1
ea53173 -
Training in progress, epoch 1
ba272a2 -
Training in progress, epoch 1
4b02318 -
Training in progress, epoch 1
d96f792 -
Training in progress, epoch 1
1e032af
-
initial commit
7e2a29e