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
Upload special_tokens_map.json with huggingface_hub
Browse files- special_tokens_map.json +7 -0
special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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