Instructions to use MultiBertGunjanPatrick/multiberts-seed-0-1200k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MultiBertGunjanPatrick/multiberts-seed-0-1200k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-0-1200k") model = AutoModelForPreTraining.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-0-1200k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MultiBertGunjanPatrick/multiberts-seed-0-1200k: direct link, hf CLI and curl.
- Browser
- Download file 441 MB
-
https://huggingface.co/MultiBertGunjanPatrick/multiberts-seed-0-1200k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MultiBertGunjanPatrick/multiberts-seed-0-1200k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MultiBertGunjanPatrick/multiberts-seed-0-1200k/resolve/main/pytorch_model.bin
441 MB
- Xet hash:
- 3d7429fa8b71d3cfb3917f9b8e864c6dcec14f03b3354f9034ddd8e8cbe2dfcf
- Size of remote file:
- 441 MB
- SHA256:
- a5824ddac7038afed9e7a6f286ac7d48387e26aa678b526f831f07a0f683cdd2
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