Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use oscarwu/label-transfer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oscarwu/label-transfer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="oscarwu/label-transfer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("oscarwu/label-transfer") model = AutoModelForSequenceClassification.from_pretrained("oscarwu/label-transfer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e6d4d1750bc0aaf1897b0fcb30ef9d2319e4246ca869ba77c777694e632b7b6
- Size of remote file:
- 1.11 GB
- SHA256:
- 4844075823523fd78befd910ba34131b2a90bce6573d841a928f100cb77e4565
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