Instructions to use AnonymousSub/dummy_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousSub/dummy_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousSub/dummy_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousSub/dummy_2") model = AutoModelForSequenceClassification.from_pretrained("AnonymousSub/dummy_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03adb5854a1582d13f698018f0323f897b19dfa86eaab20a70036d3a5aaf1373
- Size of remote file:
- 1.42 GB
- SHA256:
- cd483d8612006b55bd93a4228e6e1601ad4f4aff0ade3751b96f7507c1d7710f
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