Instructions to use Ramzey/BERTChechiaMasked with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ramzey/BERTChechiaMasked with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Ramzey/BERTChechiaMasked")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Ramzey/BERTChechiaMasked") model = AutoModelForMaskedLM.from_pretrained("Ramzey/BERTChechiaMasked", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 793f67d8bc4531c16bffb7bd4e971a9e40395478dffeb138827b1b18906e7e6a
- Size of remote file:
- 334 MB
- SHA256:
- a211527b5ddce91f8148456c5ef871f672dc4d152db134eeeba558d510994fd1
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