Instructions to use digitalwas-developer/Fail-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use digitalwas-developer/Fail-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="digitalwas-developer/Fail-1B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("digitalwas-developer/Fail-1B") model = AutoModelForSequenceClassification.from_pretrained("digitalwas-developer/Fail-1B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bd23fc262bd22d01de6702752ae58249daafe909514d038f7c86c40fbb926ca
- Size of remote file:
- 557 MB
- SHA256:
- dd04a336f8c5e1c7d917396461cfc421d2babcaca3e67ef18084ec305e97029e
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