Transformers
PyTorch
TensorFlow
English
bert
pretraining
multiberts
multiberts-seed_1
multiberts-seed_1-step_700k
Instructions to use google/multiberts-seed_1-step_700k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/multiberts-seed_1-step_700k with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("google/multiberts-seed_1-step_700k") model = AutoModelForPreTraining.from_pretrained("google/multiberts-seed_1-step_700k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 892f79c9fe9d9bda6220bd510a10cea8be1763121d0e4d9ad44914fff6e2ad9a
- Size of remote file:
- 441 MB
- SHA256:
- 0dabaff7db591c0d4fbcd255083a721a056c7d91b92df8a9475d60f2fbc435c1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.