Instructions to use paritc/multilabelclassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paritc/multilabelclassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="paritc/multilabelclassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("paritc/multilabelclassification") model = AutoModelForSequenceClassification.from_pretrained("paritc/multilabelclassification") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
380bae7 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:47b3d9d3f1a3e36f1af022f39449c21a1757d4372c62f85f61b55d51ddfb9803
size 437986332
|