Text Classification
Transformers
PyTorch
English
medicoder_complete
medical
healthcare
clinical-notes
medical-coding
few-shot-learning
prototypical-networks
deployment-ready
self-contained
Instructions to use sshan95/medicoder-ai-v4-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshan95/medicoder-ai-v4-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sshan95/medicoder-ai-v4-model")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sshan95/medicoder-ai-v4-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2dca5432e130dced19cda70376036747966108e1f23ba415c607d2e21f238bb
- Size of remote file:
- 630 MB
- SHA256:
- a3efe1657a4bd5baf1950a82495bac8d9f45e27045d2b6d2b0bf0a96e16e2504
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