Instructions to use MultiBertGunjanPatrick/multiberts-seed-1-1600k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MultiBertGunjanPatrick/multiberts-seed-1-1600k with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-1-1600k") model = AutoModelForPreTraining.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-1-1600k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MultiBertGunjanPatrick/multiberts-seed-1-1600k: direct link, hf CLI and curl.
- Browser
- Download file 441 MB
-
https://huggingface.co/MultiBertGunjanPatrick/multiberts-seed-1-1600k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MultiBertGunjanPatrick/multiberts-seed-1-1600k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MultiBertGunjanPatrick/multiberts-seed-1-1600k/resolve/main/pytorch_model.bin
441 MB
- Xet hash:
- 5fb327ae4214aa84484e6c2ed7c34b14f654962b32901539a42752b4e16012f6
- Size of remote file:
- 441 MB
- SHA256:
- f5dbec986111b83d1b0a3b3a437dc4e489069ab39ee7150dfaf24e207a3a9685
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