Instructions to use gianma/fakeNewsBERTClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gianma/fakeNewsBERTClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gianma/fakeNewsBERTClassifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gianma/fakeNewsBERTClassifier") model = AutoModelForSequenceClassification.from_pretrained("gianma/fakeNewsBERTClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gianma/fakeNewsBERTClassifier: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/gianma/fakeNewsBERTClassifier/resolve/main/training_args.bin
- Command line
-
hf download hf://gianma/fakeNewsBERTClassifier/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/gianma/fakeNewsBERTClassifier/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- c95020764b4abf347b3bec4998bb90b32920641fa79eb7471eb0c30d825070d0
- Size of remote file:
- 3.9 kB
- SHA256:
- 6c0f44d7026e2db280c4a02924000d254d32274b3aa4f3ff86fd0b336bea6a53
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