Instructions to use OliverHeine/albert-base-v2_fold_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/albert-base-v2_fold_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/albert-base-v2_fold_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/albert-base-v2_fold_4") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/albert-base-v2_fold_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4f9eec9a0aa94f0ce3294c1780eb690f298ed44f942d19b3a9579ce8e43f5ed
- Size of remote file:
- 5.27 kB
- SHA256:
- 089f46da009f0378075b37d4ca8950fb3be431263fb7854095c74804bc2574eb
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