Instructions to use albert/albert-base-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-base-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-base-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-base-v1") model = AutoModelForMaskedLM.from_pretrained("albert/albert-base-v1") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0da8c9e189b2bda524546a6e0d96fa9cde1ee10d1f4b005aa71f08565a1bd467
- Size of remote file:
- 47.4 MB
- SHA256:
- 051305f01a2699dbc89279d6849234d7677d40cdf7ad1b41e635d9c189111ad8
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