Instructions to use kvsr/merged-model-sequence-classification-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kvsr/merged-model-sequence-classification-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kvsr/merged-model-sequence-classification-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kvsr/merged-model-sequence-classification-binary") model = AutoModelForSequenceClassification.from_pretrained("kvsr/merged-model-sequence-classification-binary") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("kvsr/merged-model-sequence-classification-binary")
model = AutoModelForSequenceClassification.from_pretrained("kvsr/merged-model-sequence-classification-binary")Quick Links
No model card
- Downloads last month
- 3
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kvsr/merged-model-sequence-classification-binary")