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:
- fe42aa5a770c6b1f8322d325d182c1cdf108e108a99fabf02a185148c9d67c0d
- Size of remote file:
- 71.5 MB
- SHA256:
- 9c67a6fa12e38e205273eb0dcc8c0aa7326dc962a5cd7a375e780f95558b830d
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