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:
- efc7e79f5bab3f1747de6fbad567fbb9f8fd8f86ad95b545b3a7d9197e30dd07
- Size of remote file:
- 3.64 kB
- SHA256:
- ab46cb2e778037a7d417b8b71512f97216787f5655fa2e07e760ec8c31baa009
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