Instructions to use Arjun24420/BERT-FakeNews-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arjun24420/BERT-FakeNews-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Arjun24420/BERT-FakeNews-Classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arjun24420/BERT-FakeNews-Classification") model = AutoModelForSequenceClassification.from_pretrained("Arjun24420/BERT-FakeNews-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Arjun24420/BERT-FakeNews-Classification: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Arjun24420/BERT-FakeNews-Classification/resolve/main/training_args.bin
- Command line
-
hf download hf://Arjun24420/BERT-FakeNews-Classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Arjun24420/BERT-FakeNews-Classification/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 1838e48e4c7c4451f8002eefc00ab2a3632a54cedc2b4ef88a160ba14bcc15dc
- Size of remote file:
- 4.54 kB
- SHA256:
- b8f0c609d07c6b1b31f5a51f4a01222990346b5cf4db1cc174b269523147cfac
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