Instructions to use JonasGeiping/crammed-bert-legacy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JonasGeiping/crammed-bert-legacy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JonasGeiping/crammed-bert-legacy")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForPreTraining model = AutoModelForPreTraining.from_pretrained("JonasGeiping/crammed-bert-legacy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from JonasGeiping/crammed-bert-legacy: direct link, hf CLI and curl.
- Browser
- Download file 481 MB
-
https://huggingface.co/JonasGeiping/crammed-bert-legacy/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://JonasGeiping/crammed-bert-legacy/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/JonasGeiping/crammed-bert-legacy/resolve/main/pytorch_model.bin
481 MB
- Xet hash:
- 03b7b520e2541ce9c09d8668c8becccc50946d3e9cd5814bbff9db394f0942ec
- Size of remote file:
- 481 MB
- SHA256:
- e71cae171394fad6e0e3d78f3959809de0d2b45c72c7b1f3218f9cafcbae4397
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