Instructions to use Mathlesage/euroBert601 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathlesage/euroBert601 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Mathlesage/euroBert601", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Mathlesage/euroBert601", trust_remote_code=True) model = AutoModel.from_pretrained("Mathlesage/euroBert601", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76562bc677c763fefd10be72a382620cb2b477d1b9738d90a0f14eaa8a594cd2
- Size of remote file:
- 17.2 MB
- SHA256:
- b31d6161193afec1abf37132af302b0545c7de27b9afdb200840bca84fa95dfd
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