Instructions to use martincc98/bert_a3_final_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use martincc98/bert_a3_final_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="martincc98/bert_a3_final_2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("martincc98/bert_a3_final_2") model = AutoModelForMaskedLM.from_pretrained("martincc98/bert_a3_final_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8316c83a2c59f370db6aea113e8a209fee3d88097143cedbac6f60c1ba858e0b
- Size of remote file:
- 436 MB
- SHA256:
- a0a4480cd437336737fd50c50401e2b6df8ecb2edcfd9a14e2b71ee9b3664698
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