Feature Extraction
Transformers
Safetensors
English
bert
text-classification
icd10
healthcare
medical
custom_code
text-embeddings-inference
Instructions to use UMCU/ICD10_classifier_base_English with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UMCU/ICD10_classifier_base_English with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="UMCU/ICD10_classifier_base_English", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UMCU/ICD10_classifier_base_English", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("UMCU/ICD10_classifier_base_English", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from UMCU/ICD10_classifier_base_English: direct link, hf CLI and curl.
- Browser
- Download file 706 kB
-
https://huggingface.co/UMCU/ICD10_classifier_base_English/resolve/main/tokenizer.json
- Command line
-
hf download hf://UMCU/ICD10_classifier_base_English/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/UMCU/ICD10_classifier_base_English/resolve/main/tokenizer.json
706 kB
File too large to display, you can check the raw version instead.