Instructions to use HyoungGeun/BERT_situation_ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HyoungGeun/BERT_situation_ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HyoungGeun/BERT_situation_")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HyoungGeun/BERT_situation_") model = AutoModelForTokenClassification.from_pretrained("HyoungGeun/BERT_situation_", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HyoungGeun/BERT_situation_: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/HyoungGeun/BERT_situation_/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HyoungGeun/BERT_situation_/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HyoungGeun/BERT_situation_/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- d34b9db5bb49cd6fd8bfe76b2788177d2fbd4ccdfa65a7d178bee695e1a913ea
- Size of remote file:
- 436 MB
- SHA256:
- e2832bd020db6d63d43a709b95de15daf23add48df3a768e933baac77e198081
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