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:
- 1d419a61ec8062af1b4ac2da2cd8468eebf2efc0002dd2cd9729a42dd28068b8
- Size of remote file:
- 1.11 GB
- SHA256:
- 585aa80d140d57312be73d228f8ad5ee5a3e0ef28bc72107a8e7f1a6675f23ca
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