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:
- c5091256b07f6497412d880ceb604b109e8f6fad1a3109afe92a60ffe220d016
- Size of remote file:
- 17.1 MB
- SHA256:
- b3b87c4cbf6f0e5b125915a0358f5ad8bbd41ad7cbe937c2afd368d4b5ff8b26
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