Instructions to use albert/albert-xxlarge-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-xxlarge-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-xxlarge-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-xxlarge-v1") model = AutoModelForMaskedLM.from_pretrained("albert/albert-xxlarge-v1", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72849e82ed45e41ea0348d12fea169fae0bf49a11dc65f82cc10f25bfe9b6a05
- Size of remote file:
- 893 MB
- SHA256:
- c2618fd9fefb8f358ee5159cc459f3537326593884f75a73bb4ba89262b71de6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.