Instructions to use gszabo/base_webcorpus3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/base_webcorpus3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/base_webcorpus3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/base_webcorpus3") model = AutoModelForMaskedLM.from_pretrained("gszabo/base_webcorpus3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gszabo/base_webcorpus3: direct link, hf CLI and curl.
- Browser
- Download file 554 MB
-
https://huggingface.co/gszabo/base_webcorpus3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gszabo/base_webcorpus3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gszabo/base_webcorpus3/resolve/main/pytorch_model.bin
554 MB
- Xet hash:
- 55194cdfdffb437462ddb017700ca2a134cb6f8087162ff00a8b3996b07b683f
- Size of remote file:
- 554 MB
- SHA256:
- 5bd482a242c2f280d3e40ab58cf37fd6b4e9f18510e62b9f85f31bbd612ced9b
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