Instructions to use gszabo/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/test") model = AutoModelForMaskedLM.from_pretrained("gszabo/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gszabo/test: direct link, hf CLI and curl.
- Browser
- Download file 626 MB
-
https://huggingface.co/gszabo/test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gszabo/test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gszabo/test/resolve/main/pytorch_model.bin
626 MB
- Xet hash:
- 5a2bc17547e5e26e12edeb85fb7d98f1606233ddb0c3e6dd1f79346cce6926af
- Size of remote file:
- 626 MB
- SHA256:
- c9ad58b9dd148d674931a001442d370176fb3e8a05032e1d8936ce9848c4e951
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