Instructions to use albert/albert-xlarge-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-xlarge-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-xlarge-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-xlarge-v1") model = AutoModelForMaskedLM.from_pretrained("albert/albert-xlarge-v1") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e086d27885b6037dff4124f5b653cfeeb2d1f641a3b121f3f07c562063e8de89
- Size of remote file:
- 236 MB
- SHA256:
- 60b7d15d319de082ab1ed81bfc26c822422ae2a66e46a752f7f609072744cfb7
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