Text Classification
Transformers
PyTorch
English
roberta
Tweet
Twitter
Clickbait
Spam
text-embeddings-inference
Instructions to use Stremie/roberta-base-clickbait with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Stremie/roberta-base-clickbait with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Stremie/roberta-base-clickbait")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Stremie/roberta-base-clickbait") model = AutoModelForSequenceClassification.from_pretrained("Stremie/roberta-base-clickbait", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Stremie/roberta-base-clickbait: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Stremie/roberta-base-clickbait/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Stremie/roberta-base-clickbait/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Stremie/roberta-base-clickbait/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- b7a8ffa2c844952c4e7e2a9d4d9adcad4e8d5bdc8313f30e68b4eeebc9f60bea
- Size of remote file:
- 499 MB
- SHA256:
- 8da4046e2a62cf2d186ee32aff6583f95bc9d33dd59dea6bf5339d210f903ef7
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