Instructions to use gszabo/base_webcorpus2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/base_webcorpus2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/base_webcorpus2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/base_webcorpus2") model = AutoModelForMaskedLM.from_pretrained("gszabo/base_webcorpus2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gszabo/base_webcorpus2: direct link, hf CLI and curl.
- Browser
- Download file 603 MB
-
https://huggingface.co/gszabo/base_webcorpus2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gszabo/base_webcorpus2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gszabo/base_webcorpus2/resolve/main/pytorch_model.bin
603 MB
- Xet hash:
- 5973ed3a1c21ff0614954f57c6f4bdab418de132f23e7e0f14eabe2e0cb1321d
- Size of remote file:
- 603 MB
- SHA256:
- 42e369f17bca6b7cedc68d689e1e74b25bd40e3549f5f3b6019934ff400ccc2c
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