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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-base-v1") model = AutoModelForMaskedLM.from_pretrained("albert/albert-base-v1", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:051305f01a2699dbc89279d6849234d7677d40cdf7ad1b41e635d9c189111ad8
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size 47376396
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