Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use wnic00/hihu4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wnic00/hihu4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wnic00/hihu4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wnic00/hihu4") model = AutoModelForSequenceClassification.from_pretrained("wnic00/hihu4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9abbc27d29e2066490f4ea8ad72dde468d5dab40918a846d54975be329e48185
- Size of remote file:
- 1.11 GB
- SHA256:
- 031eabdaef48179ea909ef53c433bf7b6794c488b1da788a3feff0cf95362934
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