Instructions to use OliverHeine/albert-base-v2_fold_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/albert-base-v2_fold_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/albert-base-v2_fold_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/albert-base-v2_fold_1") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/albert-base-v2_fold_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d640fedc8a80d1846dc4df1c2ff42518f706d9d9f577b4b4f7426a57ef8a0174
- Size of remote file:
- 5.27 kB
- SHA256:
- 8d9e4530e1384397620e90efa424567ad55e443faeb5e48b3b0a437d858a9b7c
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