Instructions to use jaimin/parrot_adequacy_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaimin/parrot_adequacy_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jaimin/parrot_adequacy_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jaimin/parrot_adequacy_model") model = AutoModelForSequenceClassification.from_pretrained("jaimin/parrot_adequacy_model") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("jaimin/parrot_adequacy_model")
model = AutoModelForSequenceClassification.from_pretrained("jaimin/parrot_adequacy_model")Quick Links
Parrot THIS IS AN ANCILLARY MODEL FOR PARROT PARAPHRASER
- What is Parrot? Parrot is a paraphrase-based utterance augmentation framework purpose-built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jaimin/parrot_adequacy_model")