Instructions to use negfir/Bert2layer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use negfir/Bert2layer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="negfir/Bert2layer")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("negfir/Bert2layer") model = AutoModelForMaskedLM.from_pretrained("negfir/Bert2layer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f19365c5afc34577e4918f6eec95883a4f71ad5846d2a2ab115acf9c805bb3c2
- Size of remote file:
- 155 MB
- SHA256:
- 362bde46d874033b469fb5236e96a4d08461718b156a1fc912bf11144f5a99bc
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