Instructions to use gszabo/base_webcorpus4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/base_webcorpus4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/base_webcorpus4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/base_webcorpus4") model = AutoModelForMaskedLM.from_pretrained("gszabo/base_webcorpus4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gszabo/base_webcorpus4: direct link, hf CLI and curl.
- Browser
- Download file 554 MB
-
https://huggingface.co/gszabo/base_webcorpus4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gszabo/base_webcorpus4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gszabo/base_webcorpus4/resolve/main/pytorch_model.bin
554 MB
- Xet hash:
- 810d7fdbc319ef25134f04a62b6a7ff772a7807627985c1882b626c7fc01e640
- Size of remote file:
- 554 MB
- SHA256:
- 39962e6ee6da973b8e590925b57869629c1eb2033fa1c10b62dd5ca7a9587594
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