Instructions to use seiya/oubiobert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seiya/oubiobert-base-uncased with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("seiya/oubiobert-base-uncased") model = AutoModelForPreTraining.from_pretrained("seiya/oubiobert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from seiya/oubiobert-base-uncased: direct link, hf CLI and curl.
- Browser
- Download file 445 MB
-
https://huggingface.co/seiya/oubiobert-base-uncased/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://seiya/oubiobert-base-uncased/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/seiya/oubiobert-base-uncased/resolve/main/flax_model.msgpack
445 MB
- Xet hash:
- e91de841b764e1f8bde0349ef7f51d69709acb5ce5016b632c8624eb02fd80d5
- Size of remote file:
- 445 MB
- SHA256:
- fd17e68a6b9dadfa19206c0a378d5dbfc45ea5a35a86931a7fabf4f1bebc06de
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