Instructions to use NeilZhong/bert-base-cased-wikitext2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeilZhong/bert-base-cased-wikitext2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NeilZhong/bert-base-cased-wikitext2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NeilZhong/bert-base-cased-wikitext2") model = AutoModelForMaskedLM.from_pretrained("NeilZhong/bert-base-cased-wikitext2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72d4f61955810096addf377a805469aa1348949b1f2c33c236d096d98765f8ec
- Size of remote file:
- 433 MB
- SHA256:
- 36a8d6826a4fb64575f3f4a558393f04a83fdba48dd2588a27e9251185985b09
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