Instructions to use albert/albert-large-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-large-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-large-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-large-v1") model = AutoModelForMaskedLM.from_pretrained("albert/albert-large-v1") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd08805c06721d4a99cd2f91cb6c5654b6c1c3b3e290188c6c1b3ba8bc9cc8e2
- Size of remote file:
- 87.2 MB
- SHA256:
- 953942d1dc42b615ed1c5f8c0ade9dd26978e2c1978f31d98f0bf441584f821d
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