Instructions to use joniponi/multilabel_inpatient_comments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joniponi/multilabel_inpatient_comments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joniponi/multilabel_inpatient_comments")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joniponi/multilabel_inpatient_comments") model = AutoModelForSequenceClassification.from_pretrained("joniponi/multilabel_inpatient_comments", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
add tokenizer
b1e7b98 -
add model
3c4103b -
Training in progress, epoch 1
98c36f1
-
Upload training_args.bin with git-lfs
5cf61eb -
add tokenizer
8f19147 -
add model
7858f3e
-
Upload training_args.bin with git-lfs
b2a4102 -
add tokenizer
f4b0b09 -
add model
ffc50b5 -
initial commit
8061480