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 training_args.bin from rseeto/multilabel_disease_bert_classification: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/rseeto/multilabel_disease_bert_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://rseeto/multilabel_disease_bert_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rseeto/multilabel_disease_bert_classification/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- d2d0939a286ecd35018df137e22b0dcc57572b35aca7de4d9651ca772409e8d7
- Size of remote file:
- 5.78 kB
- SHA256:
- f2c13c3f73c67a7fab5b56c1ba029bf87a7e635ae7273e6d171ed61416cef96b
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