Instructions to use Tomohiro/RealMedNLP_CR_JA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tomohiro/RealMedNLP_CR_JA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tomohiro/RealMedNLP_CR_JA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tomohiro/RealMedNLP_CR_JA") model = AutoModelForTokenClassification.from_pretrained("Tomohiro/RealMedNLP_CR_JA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Tomohiro/RealMedNLP_CR_JA: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/Tomohiro/RealMedNLP_CR_JA/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Tomohiro/RealMedNLP_CR_JA/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Tomohiro/RealMedNLP_CR_JA/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- fa45ba51583b67d38b8c1be00a4147f093ee602a116b803fa17f85545e2d7033
- Size of remote file:
- 440 MB
- SHA256:
- ccce71084b8f6e81415e8f8e07cf27f59087aa2fda02c296959322ef8acb8a6a
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