Instructions to use harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedNoPreTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedNoPreTrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedNoPreTrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedNoPreTrain") model = AutoModelForMaskedLM.from_pretrained("harish/AStitchInLanguageModels-Task2_EN_BERTTokenizedNoPreTrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
060fcb8 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:c9377fbdc75e1ac1f03a62c26d2d866f8811234e695bc49c6e250b6501bbbfea
size 433413083
|