Instructions to use ielabgroup/StandardBERT-DR-ST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ielabgroup/StandardBERT-DR-ST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ielabgroup/StandardBERT-DR-ST")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ielabgroup/StandardBERT-DR-ST") model = AutoModel.from_pretrained("ielabgroup/StandardBERT-DR-ST", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ielabgroup/StandardBERT-DR-ST: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/ielabgroup/StandardBERT-DR-ST/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ielabgroup/StandardBERT-DR-ST/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ielabgroup/StandardBERT-DR-ST/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- a33b59a4ff5786fbc4b13a3bb54262d61835a5d9cf09f0aec9c510b6f9aac50c
- Size of remote file:
- 438 MB
- SHA256:
- a8dd2e6774a8f2744319b578bcc73ba432f2263fe29c2d0bfb8b2464b38e0e00
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