Instructions to use gszabo/base_subtoken10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/base_subtoken10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/base_subtoken10")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/base_subtoken10") model = AutoModelForMaskedLM.from_pretrained("gszabo/base_subtoken10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gszabo/base_subtoken10: direct link, hf CLI and curl.
- Browser
- Download file 375 MB
-
https://huggingface.co/gszabo/base_subtoken10/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gszabo/base_subtoken10/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gszabo/base_subtoken10/resolve/main/pytorch_model.bin
375 MB
- Xet hash:
- 375621b228cc0e23ec4c8b01565a1ed18f871d407b5adcf662c5657bb21a6edd
- Size of remote file:
- 375 MB
- SHA256:
- 9ed0a1f1f4021acaa5d5eedca3d2b006dc31481747ad7282b7dfdf48d73e6025
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