Transformers
PyTorch
TensorFlow
English
bert
pretraining
multiberts
multiberts-seed_4
multiberts-seed_4-step_500k
Instructions to use google/multiberts-seed_4-step_500k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/multiberts-seed_4-step_500k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("google/multiberts-seed_4-step_500k") model = AutoModelForPreTraining.from_pretrained("google/multiberts-seed_4-step_500k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from google/multiberts-seed_4-step_500k: direct link, hf CLI and curl.
- Browser
- Download file 536 MB
-
https://huggingface.co/google/multiberts-seed_4-step_500k/resolve/main/tf_model.h5
- Command line
-
hf download hf://google/multiberts-seed_4-step_500k/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/google/multiberts-seed_4-step_500k/resolve/main/tf_model.h5
536 MB
- Xet hash:
- ee8eb00e70571b53f3424c3a147fbc286697402d7ae486736b7189b3cfc31684
- Size of remote file:
- 536 MB
- SHA256:
- 0064bd116eef1fe46ef8348392c84d6c56dbd09f54b831db8689c3ab751ced75
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