Instructions to use Rustem/roberta-base-trained-43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rustem/roberta-base-trained-43 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rustem/roberta-base-trained-43")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rustem/roberta-base-trained-43") model = AutoModelForMaskedLM.from_pretrained("Rustem/roberta-base-trained-43", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Rustem/roberta-base-trained-43: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/Rustem/roberta-base-trained-43/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Rustem/roberta-base-trained-43@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Rustem/roberta-base-trained-43/resolve/refs%2Fpr%2F1/training_args.bin
2.99 kB
- Xet hash:
- 2846672bfb63b645d48c684c604820d89ded699e4f48ddcc7a1ee018e67a38e3
- Size of remote file:
- 2.99 kB
- SHA256:
- 3bb35a6474506580e4cf60cefd3d006fb711f4d06da2a530169f33fd5d81ce08
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