Instructions to use OliverHeine/albert-base-v2_fold_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/albert-base-v2_fold_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/albert-base-v2_fold_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/albert-base-v2_fold_3") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/albert-base-v2_fold_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0fa35db6607b63e574ff95fd3d6271d2b1070ba96b0e521368e3348c30d8c02
- Size of remote file:
- 5.27 kB
- SHA256:
- 7b0ef33c16c50f22bd7048282a5a7a2b1e20352561e89f4e3248e772fd76cc2e
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