Instructions to use OliverHeine/albert-base-v2_fold_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/albert-base-v2_fold_0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/albert-base-v2_fold_0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/albert-base-v2_fold_0") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/albert-base-v2_fold_0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8414c4ba8eb64982a0c46c0a416d0a3302e02e60878156568c4dc6646737aced
- Size of remote file:
- 5.27 kB
- SHA256:
- 74b802aafbf27401d3eeb0f894bf450118e04f23f6dce5ad6f0f8d09c5edea69
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