Instructions to use versae/roberta-base-ncc-512b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/roberta-base-ncc-512b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="versae/roberta-base-ncc-512b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("versae/roberta-base-ncc-512b") model = AutoModelForMaskedLM.from_pretrained("versae/roberta-base-ncc-512b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from versae/roberta-base-ncc-512b: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/versae/roberta-base-ncc-512b/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://versae/roberta-base-ncc-512b/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/versae/roberta-base-ncc-512b/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- 9d32ca45771303b9753b9612491504d24486b42dbd31c20e2dc073aaaaba13b1
- Size of remote file:
- 499 MB
- SHA256:
- b973b8f46e005ee02f6ba580dbba6b3800f61749eae1eea4a455000847dc0578
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