Instructions to use TheJournal/Opposite_Day with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheJournal/Opposite_Day with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TheJournal/Opposite_Day")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TheJournal/Opposite_Day") model = AutoModelForSequenceClassification.from_pretrained("TheJournal/Opposite_Day", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TheJournal/Opposite_Day: direct link, hf CLI and curl.
- Browser
- Download file 247 Bytes
-
https://huggingface.co/TheJournal/Opposite_Day/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TheJournal/Opposite_Day/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TheJournal/Opposite_Day/resolve/main/pytorch_model.bin
247 Bytes
- Xet hash:
- dec5021de8ac3ea952e47a3087186101127e530dae7cc42f0873c1c732143a09
- Size of remote file:
- 247 Bytes
- SHA256:
- 686e44a75bdaff01162eb0af3e7b20231fbe9e887d78bd390e29a8bee53351f7
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