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:
- 3cbc0b4a5cbfa4e917530dcecc36759fb0ad76f221eec6d0e93d5a3fab6ead00
- Size of remote file:
- 71.5 MB
- SHA256:
- d71144e2bff6df2ebb06e247fbb653859abb609fe1effc9923ada5fc9df255e8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.