Instructions to use ielabgroup/StandardBERT-DR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ielabgroup/StandardBERT-DR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ielabgroup/StandardBERT-DR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ielabgroup/StandardBERT-DR") model = AutoModel.from_pretrained("ielabgroup/StandardBERT-DR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ielabgroup/StandardBERT-DR: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/ielabgroup/StandardBERT-DR/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ielabgroup/StandardBERT-DR/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ielabgroup/StandardBERT-DR/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- fcd69cdfd596c155d62ea1d9be0d236ffbf4cd0309cd990110b653cfdf6d5b34
- Size of remote file:
- 438 MB
- SHA256:
- 8bbad62adb64a7be70d225b002c9bcc80995722bd29f4bb13912d43b7e9756bc
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