Instructions to use nlpodyssey/bert-multilingual-uncased-intelligence-headlines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpodyssey/bert-multilingual-uncased-intelligence-headlines with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nlpodyssey/bert-multilingual-uncased-intelligence-headlines")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nlpodyssey/bert-multilingual-uncased-intelligence-headlines") model = AutoModelForSequenceClassification.from_pretrained("nlpodyssey/bert-multilingual-uncased-intelligence-headlines") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bdc9e67bf9ff8b7a0355e4895ef940c496fccf7ec5e85e038bdfc1551b5a989
- Size of remote file:
- 670 MB
- SHA256:
- 1bee5c6fdccee72e394847ba2bb78afdb25c0f016f1e953f875fdf7be577816e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.