Instructions to use gszabo/base_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/base_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/base_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/base_test") model = AutoModelForMaskedLM.from_pretrained("gszabo/base_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gszabo/base_test: direct link, hf CLI and curl.
- Browser
- Download file 627 MB
-
https://huggingface.co/gszabo/base_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gszabo/base_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gszabo/base_test/resolve/main/pytorch_model.bin
627 MB
- Xet hash:
- 770f7147b0a2f54642bf4b29f64085c28e311d3359d1aa0f203b78aace74999e
- Size of remote file:
- 627 MB
- SHA256:
- ee1f8c11e94101125924084cd9a03882193bd41df2a53fb494833d51429af1a1
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