Instructions to use research-dump/albert-base-v2_fold_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/albert-base-v2_fold_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/albert-base-v2_fold_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/albert-base-v2_fold_1") model = AutoModelForSequenceClassification.from_pretrained("research-dump/albert-base-v2_fold_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 555f23db1f24d7d57fbdd8a2683a72c22c0e687314fd1c2a55e2e4635c14ffee
- Size of remote file:
- 760 kB
- SHA256:
- fefb02b667a6c5c2fe27602d28e5fb3428f66ab89c7d6f388e7c8d44a02d0336
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