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 scheduler.pt from Rustem/roberta-base-trained-43: direct link, hf CLI and curl.
- Browser
- Download file 623 Bytes
-
https://huggingface.co/Rustem/roberta-base-trained-43/resolve/main/scheduler.pt
- Command line
-
hf download hf://Rustem/roberta-base-trained-43/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/Rustem/roberta-base-trained-43/resolve/main/scheduler.pt
623 Bytes
- Xet hash:
- a0ab6cd151233ccf7cf2696199e0b7bf600d5563a289385a678ed4bd7d51914e
- Size of remote file:
- 623 Bytes
- SHA256:
- ec3427f0b34de6153a1817fbec41ba66a766753fa4133435ea94a8bc4577f393
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