Instructions to use klue/roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use klue/roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="klue/roberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("klue/roberta-large") model = AutoModelForMaskedLM.from_pretrained("klue/roberta-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from klue/roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 1.35 GB
-
https://huggingface.co/klue/roberta-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://klue/roberta-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/klue/roberta-large/resolve/main/pytorch_model.bin
1.35 GB
- Xet hash:
- fc03a8a66e3dc56f4e5770eecc2c89936a05c911a32192e9c627e084a14394cf
- Size of remote file:
- 1.35 GB
- SHA256:
- fd6ebf63041d35e4dd5f9676827c10bca5b63b77644e9da8bd24801b621b7876
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