Instructions to use Elbe/RoBERTaforIns with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Elbe/RoBERTaforIns with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Elbe/RoBERTaforIns")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Elbe/RoBERTaforIns") model = AutoModelForMaskedLM.from_pretrained("Elbe/RoBERTaforIns", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Elbe/RoBERTaforIns: direct link, hf CLI and curl.
- Browser
- Download file 1.78 kB
-
https://huggingface.co/Elbe/RoBERTaforIns/resolve/main/training_args.bin
- Command line
-
hf download hf://Elbe/RoBERTaforIns/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Elbe/RoBERTaforIns/resolve/main/training_args.bin
1.78 kB
- Xet hash:
- 65f92934d5f0ceb43ba26e7f8a4451f400e08e6a586581014d9ab37627e4c428
- Size of remote file:
- 1.78 kB
- SHA256:
- 334bf0a9cc6d76ef6edf8c1b50c0561a6cd87351f3d610e8e45ca354de8b7dad
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