Instructions to use eunjin/bert_base_cased_syntax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eunjin/bert_base_cased_syntax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="eunjin/bert_base_cased_syntax")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("eunjin/bert_base_cased_syntax") model = AutoModel.from_pretrained("eunjin/bert_base_cased_syntax", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eunjin/bert_base_cased_syntax: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/eunjin/bert_base_cased_syntax/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eunjin/bert_base_cased_syntax/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eunjin/bert_base_cased_syntax/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 66bb09841ea4fe8887c9e2e482f2e0f0c501cbd897d3cd16874aba585dc85b5d
- Size of remote file:
- 433 MB
- SHA256:
- 8a60f073975e6693cbce3bf2bee7c1beea5c435c82ad691599269eb72ffcdf6d
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