Instructions to use improz4/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use improz4/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="improz4/model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("improz4/model") model = AutoModelForMaskedLM.from_pretrained("improz4/model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4414a2907ed098b86e220ebf6d13c75a4cfb9c03acfcee099b47f8075b7b5273
- Size of remote file:
- 30.3 MB
- SHA256:
- e797a0c9d4c25d91bb181c06cf436eb24ab4e10fbab37581b98605c50717892d
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