Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use wnic00/hihu2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wnic00/hihu2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wnic00/hihu2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wnic00/hihu2") model = AutoModelForSequenceClassification.from_pretrained("wnic00/hihu2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd565c56c721abaffbb5f0d376d26a71501884d830c5921c2253d66909c6a07a
- Size of remote file:
- 3.96 kB
- SHA256:
- 317e102e031b5ac7a8900b6b3638b85ce038480852fd016d5f220e9f6b7162b7
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