Instructions to use albert/albert-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-base-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-base-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-base-v2") model = AutoModelForMaskedLM.from_pretrained("albert/albert-base-v2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4beb7a221567da9a1b4a4cd68ffddb38bfab6ae76b90ccfa30cd4dd50f67c0d
- Size of remote file:
- 47.4 MB
- SHA256:
- 46704a4f59d6665d1f0c4fe5cda17dd6308beead11193d7572641166df070299
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