Instructions to use Rustem/roberta-large-copy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rustem/roberta-large-copy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rustem/roberta-large-copy")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rustem/roberta-large-copy") model = AutoModelForMaskedLM.from_pretrained("Rustem/roberta-large-copy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Rustem/roberta-large-copy: direct link, hf CLI and curl.
- Browser
- Download file 135 Bytes
-
https://huggingface.co/Rustem/roberta-large-copy/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Rustem/roberta-large-copy/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Rustem/roberta-large-copy/resolve/main/flax_model.msgpack
135 Bytes
- Xet hash:
- a6d09263079e2d5f8e599fe7b6f3141a001e5af4a079276abfdfcebaa1a41250
- Size of remote file:
- 135 Bytes
- SHA256:
- 1871411d0eeaa23419bd7a31654025bdb42ea7ff6f5d5b0de799bda607a629c8
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