Transformers
PyTorch
TensorFlow
JAX
English
bert
pretraining
singapore
sg
singlish
malaysia
ms
manglish
bert-base-uncased
Instructions to use zanelim/singbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zanelim/singbert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("zanelim/singbert") model = AutoModelForPreTraining.from_pretrained("zanelim/singbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from zanelim/singbert: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/zanelim/singbert/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://zanelim/singbert/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/zanelim/singbert/resolve/main/flax_model.msgpack
440 MB
- Xet hash:
- a8af92db33cfc059de5269f605c8378d91031102ca5101a2df1161c96bcfbaf3
- Size of remote file:
- 440 MB
- SHA256:
- 7f29f5bac02535e9b7ec8003de8769e6df808b5a74e10f20408fbbe5dce78f44
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