Instructions to use EMBEDDIA/crosloengual-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBEDDIA/crosloengual-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EMBEDDIA/crosloengual-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/crosloengual-bert") model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/crosloengual-bert") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65bc1799ba9611ac77527c17bdbf8e7da0e10ce082b63fa902752a0d1e1875e8
- Size of remote file:
- 497 MB
- SHA256:
- 7e3d879fb10aa50046f9a6fdd227e0139e375b7240f1df9a9f6c63b70f27fafe
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