Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use intanm/clickbait_classification_xlm_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intanm/clickbait_classification_xlm_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intanm/clickbait_classification_xlm_roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intanm/clickbait_classification_xlm_roberta") model = AutoModelForSequenceClassification.from_pretrained("intanm/clickbait_classification_xlm_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from intanm/clickbait_classification_xlm_roberta: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/intanm/clickbait_classification_xlm_roberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://intanm/clickbait_classification_xlm_roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/intanm/clickbait_classification_xlm_roberta/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 81c24604cb48ca2ff6a8eaeecf8c1c80b21fe9f31a57141040f2dbad6ff52595
- Size of remote file:
- 1.11 GB
- SHA256:
- f77cec38dc6f86bde1c734e3c38fe59262c32b8ddb2ae5b334f21a8dfcc00ebd
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