Instructions to use OliverHeine/albert-base-v2_fold_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/albert-base-v2_fold_8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/albert-base-v2_fold_8")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/albert-base-v2_fold_8") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/albert-base-v2_fold_8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0166154bc40cac9a88c6c4679c6e5d71d4004b0e54bac6c2867b5fa22c499e6e
- Size of remote file:
- 5.27 kB
- SHA256:
- 5283c89200e6b9c1858268658b0c2bd2ed8dc88c4d54d182723203d5c15dcad1
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