Instructions to use Taekyoon/test_bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taekyoon/test_bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Taekyoon/test_bert_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Taekyoon/test_bert_model") model = AutoModel.from_pretrained("Taekyoon/test_bert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Taekyoon/test_bert_model: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/Taekyoon/test_bert_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Taekyoon/test_bert_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Taekyoon/test_bert_model/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- d731a94b669184f6915e59a1291cb23162b4e920d185e01136e7f56ea60aaeb4
- Size of remote file:
- 443 MB
- SHA256:
- 4f31874378a0b21cd413aed0199430ed539adccabd71e6c4c9abfe32701f2f35
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