Instructions to use LDD/bert_wwm_new_ext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LDD/bert_wwm_new_ext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LDD/bert_wwm_new_ext")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LDD/bert_wwm_new_ext") model = AutoModel.from_pretrained("LDD/bert_wwm_new_ext", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from LDD/bert_wwm_new_ext: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/LDD/bert_wwm_new_ext/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://LDD/bert_wwm_new_ext/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/LDD/bert_wwm_new_ext/resolve/main/pytorch_model.bin
409 MB
- Xet hash:
- 09cd5181ebc02f274f623fdf6cb8a273f7275b58ff10c4b230334d3a03de59f8
- Size of remote file:
- 409 MB
- SHA256:
- 92504afb595b884569ee8e6d970cab92c6d8fb07b25862cbe5b6b01dffd18e77
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