Instructions to use versae/xlm-roberta-base-ncc-zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/xlm-roberta-base-ncc-zero with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="versae/xlm-roberta-base-ncc-zero")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("versae/xlm-roberta-base-ncc-zero") model = AutoModelForMaskedLM.from_pretrained("versae/xlm-roberta-base-ncc-zero", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download create_pytorch.py from versae/xlm-roberta-base-ncc-zero: direct link, hf CLI and curl.
- Browser
- Download file 106 Bytes
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https://huggingface.co/versae/xlm-roberta-base-ncc-zero/resolve/main/create_pytorch.py
- Command line
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hf download hf://versae/xlm-roberta-base-ncc-zero/create_pytorch.py
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curl -L -o create_pytorch.py https://huggingface.co/versae/xlm-roberta-base-ncc-zero/resolve/main/create_pytorch.py
106 Bytes
| from transformers import AutoModel; AutoModel.from_pretrained('./', from_flax=True).save_pretrained('./') | |