Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use davanstrien/demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davanstrien/demo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/demo") model = AutoModelForSequenceClassification.from_pretrained("davanstrien/demo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63a8ab04a3e736ae7e8af4a51ec3353ba3bf28bb15899b05b8b04e23785be8f8
- Size of remote file:
- 1.11 GB
- SHA256:
- 921387a76dc0f489088bb76700cd11348987821a7e7bc6e9d89ccb67e58d0a9f
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