Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use wnic00/hihu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wnic00/hihu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wnic00/hihu")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wnic00/hihu") model = AutoModelForSequenceClassification.from_pretrained("wnic00/hihu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e14101dec3a4d5b806cce3cb57a6dd0ea0efd2d38311e9c95f409f2cd84c75d
- Size of remote file:
- 1.11 GB
- SHA256:
- 6a307bc91397eec774a9ae93415d38c988560bbfa9d79ef62eb0bf3e78076fe2
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