Instructions to use pdelobelle/robBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pdelobelle/robBERT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pdelobelle/robBERT-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pdelobelle/robBERT-base") model = AutoModelForMaskedLM.from_pretrained("pdelobelle/robBERT-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from pdelobelle/robBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/pdelobelle/robBERT-base/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://pdelobelle/robBERT-base/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/pdelobelle/robBERT-base/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- 50b266d4c6522305a7a67bc0dad2ac6bbc2856f620cf3a1a13d7763179f67fa5
- Size of remote file:
- 499 MB
- SHA256:
- c5b43032cb2470bc16668568fe6a016b7e920424abc4f99a55f0e8601e570d15
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