Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use marianna13/link-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marianna13/link-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marianna13/link-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marianna13/link-classification") model = AutoModelForSequenceClassification.from_pretrained("marianna13/link-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4319e5d4fee0e3eb690fe98ae74cb3fbed08a811b55895860a67d10ee9ba1918
- Size of remote file:
- 2.24 GB
- SHA256:
- 7ea01eed074d82accb8c67313d2267372727e97843ce0d25d8b6795c2b586417
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