Instructions to use rseeto/multilabel_disease_bert_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rseeto/multilabel_disease_bert_classification with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased") model = PeftModel.from_pretrained(base_model, "rseeto/multilabel_disease_bert_classification") - Transformers
How to use rseeto/multilabel_disease_bert_classification with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rseeto/multilabel_disease_bert_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processed_train.csv from rseeto/multilabel_disease_bert_classification: direct link, hf CLI and curl.
- Browser
- Download file 1.16 MB
-
https://huggingface.co/rseeto/multilabel_disease_bert_classification/resolve/main/processed_train.csv
- Command line
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hf download hf://rseeto/multilabel_disease_bert_classification/processed_train.csv
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curl -L -o processed_train.csv https://huggingface.co/rseeto/multilabel_disease_bert_classification/resolve/main/processed_train.csv
1.16 MB
File too large to display, you can check the raw version instead.