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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sshan95/medicoder-ai-v4-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sshan95/medicoder-ai-v4-model: direct link, hf CLI and curl.
- Browser
- Download file 669 kB
-
https://huggingface.co/sshan95/medicoder-ai-v4-model/resolve/main/tokenizer.json
- Command line
-
hf download hf://sshan95/medicoder-ai-v4-model/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/sshan95/medicoder-ai-v4-model/resolve/main/tokenizer.json
669 kB
File too large to display, you can check the raw version instead.