Instructions to use Andrija/SRoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andrija/SRoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Andrija/SRoBERTa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Andrija/SRoBERTa") model = AutoModelForMaskedLM.from_pretrained("Andrija/SRoBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Andrija/SRoBERTa: direct link, hf CLI and curl.
- Browser
- Download file 482 MB
-
https://huggingface.co/Andrija/SRoBERTa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Andrija/SRoBERTa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Andrija/SRoBERTa/resolve/main/pytorch_model.bin
482 MB
- Xet hash:
- 8ac1e4bc689ba1ada6743eaf8240b7940db5bf694883c1b70d42d7a6a9c6f564
- Size of remote file:
- 482 MB
- SHA256:
- e49cdca272f55169d00329bcf0954449b134b1e4fcc5d98b96068f1363a3b840
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