Instructions to use albert/albert-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-large-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-large-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-large-v2") model = AutoModelForMaskedLM.from_pretrained("albert/albert-large-v2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 022219fc80f83005beab532932f59a7242e48a7622a42b41b8d6df8ef5cbbb31
- Size of remote file:
- 71.5 MB
- SHA256:
- 3a3cfb9cee0b6862dcf5f752220adcc4505d3cfd977d2448573f9ee9ddc2204c
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