Instructions to use OliverHeine/albert-base-v2_fold_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/albert-base-v2_fold_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/albert-base-v2_fold_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/albert-base-v2_fold_2") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/albert-base-v2_fold_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1b67aa4a511e9d0740314cb9ba435ca85be7a136500cdd7bfad0db8febef60e
- Size of remote file:
- 5.27 kB
- SHA256:
- 9cd227da2c5bb6c15a43c9f49a3fdb86faa081f717dec12668bf0b42cf583aad
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