Instructions to use gszabo/base2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/base2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/base2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/base2") model = AutoModelForMaskedLM.from_pretrained("gszabo/base2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gszabo/base2: direct link, hf CLI and curl.
- Browser
- Download file 627 MB
-
https://huggingface.co/gszabo/base2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gszabo/base2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gszabo/base2/resolve/main/pytorch_model.bin
627 MB
- Xet hash:
- 9c4fec1387c72a28532b0f587c2fa450e529c705b5b85ed960d9d0123674aa2c
- Size of remote file:
- 627 MB
- SHA256:
- 8a3679327cb38f9aa2965004c0da0a7f65a468312f27320223276e2dae09f349
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