Instructions to use MultiBertGunjanPatrick/multiberts-seed-0-1700k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MultiBertGunjanPatrick/multiberts-seed-0-1700k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-0-1700k") model = AutoModelForPreTraining.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-0-1700k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MultiBertGunjanPatrick/multiberts-seed-0-1700k: direct link, hf CLI and curl.
- Browser
- Download file 441 MB
-
https://huggingface.co/MultiBertGunjanPatrick/multiberts-seed-0-1700k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MultiBertGunjanPatrick/multiberts-seed-0-1700k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MultiBertGunjanPatrick/multiberts-seed-0-1700k/resolve/main/pytorch_model.bin
441 MB
- Xet hash:
- aa9ede5958a14e26663fa76cefa804de60a83ac9aaa8387fb2ace9f301d53810
- Size of remote file:
- 441 MB
- SHA256:
- a4e2c85757a10f70395328b435170628fab2f406f71554b0f1c5f190a576f637
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