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:
- 971119728037ca97b64e1f71346b6f312b3960590a742f9053e5d7868e3a07d4
- Size of remote file:
- 87.2 MB
- SHA256:
- d7f1e5823bcb91f678bfba4651e733fbc6e88929b5a6b54d8362b2098a0aba2a
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