Instructions to use google-bert/bert-large-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-large-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-large-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-large-uncased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-large-uncased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
addition of Rust model
Browse filesConverted `pytorch_model.bin` via utility in [rust-bert](https://github.com/guillaume-be/rust-bert) using following command:
```
python3 utils/convert_model.py ../pytorch_model.bin
```
**libtorch:** libtorch-cxx11-abi-shared-with-deps-2.1.0+cu118
**rust-bert** commit/1f4d344668232da8e669e7fea1391c8829d5d1e3
- rust_model.ot +3 -0
rust_model.ot
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version https://git-lfs.github.com/spec/v1
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oid sha256:9db92b28d6fb0e5ab770b24ed27bde941d1f314a3c5e8c28d698025cc1807d7f
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