Instructions to use versae/roberta-base-ncc-512c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/roberta-base-ncc-512c with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="versae/roberta-base-ncc-512c")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("versae/roberta-base-ncc-512c") model = AutoModelForMaskedLM.from_pretrained("versae/roberta-base-ncc-512c", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from versae/roberta-base-ncc-512c: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/versae/roberta-base-ncc-512c/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://versae/roberta-base-ncc-512c/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/versae/roberta-base-ncc-512c/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- 44f151b733ae911c70d302bd2de394cc5af7fd444cb1d08e924fdf601e0338fd
- Size of remote file:
- 499 MB
- SHA256:
- c50587cd77dbfe6ec450b0bf5d3ea1ed125f87d2c0b63e17ee0a88d574834298
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