Instructions to use susnato/test-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use susnato/test-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="susnato/test-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("susnato/test-bert") model = AutoModel.from_pretrained("susnato/test-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from susnato/test-bert: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/susnato/test-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://susnato/test-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/susnato/test-bert/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 65e91340019fa7816e865a55ce0ddc2dba8d51bba87f9a84cd65a67291a1e227
- Size of remote file:
- 438 MB
- SHA256:
- 1cc9ac9db60a792e6fa92cfcb498f78012d087835315c92805fb111a837b10d6
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