Instructions to use chanwoopark/roberta-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chanwoopark/roberta-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chanwoopark/roberta-binary")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chanwoopark/roberta-binary") model = AutoModelForTokenClassification.from_pretrained("chanwoopark/roberta-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from chanwoopark/roberta-binary: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/chanwoopark/roberta-binary/resolve/main/model.safetensors
- Command line
-
hf download hf://chanwoopark/roberta-binary/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/chanwoopark/roberta-binary/resolve/main/model.safetensors
496 MB
- Xet hash:
- 1d075d81b1cb87d4a8e586ed94a591c2ae11594f281f9878f49c5c19c06b567c
- Size of remote file:
- 496 MB
- SHA256:
- e407af7b91bb57a2e4c1c1f67affbb8b35a422f42e552bd227bd7ca85d68ab58
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