Instructions to use versae/roberta-base-ncc-512d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/roberta-base-ncc-512d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="versae/roberta-base-ncc-512d")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("versae/roberta-base-ncc-512d") model = AutoModelForMaskedLM.from_pretrained("versae/roberta-base-ncc-512d", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from versae/roberta-base-ncc-512d: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/versae/roberta-base-ncc-512d/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://versae/roberta-base-ncc-512d/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/versae/roberta-base-ncc-512d/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- 9c34988f7dbfd223a75ee2579991cb94eb49b1666eeaba1c1fa10f5ec4755bb5
- Size of remote file:
- 499 MB
- SHA256:
- 22074468b678d975acac656150f60cad47ef1770d4441014f399f5ded210b9ba
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