Instructions to use EuroBERT/EuroBERT-2.1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EuroBERT/EuroBERT-2.1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EuroBERT/EuroBERT-2.1B", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EuroBERT/EuroBERT-2.1B", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("EuroBERT/EuroBERT-2.1B", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b924319128df3a0d19bcb9ee0aa4e8bb34cb14dbf735ba4ab16fb20d00a7d40
- Size of remote file:
- 9.61 GB
- SHA256:
- 35a6930e42ab83871bbc55cb4a08bf071dd496d7bb89355a85aabca3a47d88d0
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