Instructions to use MultiBertGunjanPatrick/multiberts-seed-0-120k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MultiBertGunjanPatrick/multiberts-seed-0-120k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-0-120k") model = AutoModelForPreTraining.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-0-120k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MultiBertGunjanPatrick/multiberts-seed-0-120k: direct link, hf CLI and curl.
- Browser
- Download file 441 MB
-
https://huggingface.co/MultiBertGunjanPatrick/multiberts-seed-0-120k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MultiBertGunjanPatrick/multiberts-seed-0-120k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MultiBertGunjanPatrick/multiberts-seed-0-120k/resolve/main/pytorch_model.bin
441 MB
- Xet hash:
- 15fa3df6f0cd11a4080ae96b3ac80802a881ed0057d145e1fcc2bc1c8c22376e
- Size of remote file:
- 441 MB
- SHA256:
- e99d990116958358b47c5834e2d2c59cf4944a0357911fe4f1583f9bf61502af
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