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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36b3f4aaad80b9e5f018e2a9cfa550c5899834e2ba67b420e8606a6a3ac8e1e4
- Size of remote file:
- 3.96 kB
- SHA256:
- fc6bb065705f19bf20ac460ff5665e794ddc2cfe0f9f1e499430271d5c1cdac1
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