Instructions to use albert/albert-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-base-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-base-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-base-v2") model = AutoModelForMaskedLM.from_pretrained("albert/albert-base-v2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2adcccfcb440f28c16d8d710f4965d2d6acfad1cb805b617bc126a5d7f596da
- Size of remote file:
- 62.7 MB
- SHA256:
- 3b207f0b36b2d7b7388456ee42f8c469dd842939b1933003ba560ccc4c11cdfd
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