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 optimizer.pt from Rustem/roberta-base-trained-43: direct link, hf CLI and curl.
- Browser
- Download file 998 MB
-
https://huggingface.co/Rustem/roberta-base-trained-43/resolve/main/optimizer.pt
- Command line
-
hf download hf://Rustem/roberta-base-trained-43/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Rustem/roberta-base-trained-43/resolve/main/optimizer.pt
998 MB
- Xet hash:
- 728a0d7cc047a197f01ccbb793dcdcd367b73c5f52bf1e61886d9943fe8f878b
- Size of remote file:
- 998 MB
- SHA256:
- 278ee0562c0de243a378a7302e408f66f664fc5070a5cdc4f2662c4baa8978d5
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