Instructions to use Denyol/FakeNews-roberta-base-html with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Denyol/FakeNews-roberta-base-html with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Denyol/FakeNews-roberta-base-html")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Denyol/FakeNews-roberta-base-html") model = AutoModelForSequenceClassification.from_pretrained("Denyol/FakeNews-roberta-base-html", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Denyol/FakeNews-roberta-base-html: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Denyol/FakeNews-roberta-base-html/resolve/main/training_args.bin
- Command line
-
hf download hf://Denyol/FakeNews-roberta-base-html/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Denyol/FakeNews-roberta-base-html/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 7c5fd068e27a2c7375d1690d7089694ad8cc231307cc51ecaca22e30ab758165
- Size of remote file:
- 4.54 kB
- SHA256:
- c61808ffd3f93bb1e82c2311fd85751fee4847f94ee075bc4bedad7fa52c56c5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.