Instructions to use albert/albert-xlarge-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-xlarge-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-xlarge-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-xlarge-v2") model = AutoModelForMaskedLM.from_pretrained("albert/albert-xlarge-v2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c392daa1e9d76e47d8aae62e73d275eb2dbeb1f1f2fb2a9415eea8aeeb58d51a
- Size of remote file:
- 236 MB
- SHA256:
- dc42ccf84d2ce04af6a2565f155b8df2d082af985adde5dc443b4aa0598901f7
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