Instructions to use prithivida/parrot_fluency_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivida/parrot_fluency_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prithivida/parrot_fluency_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prithivida/parrot_fluency_model") model = AutoModelForSequenceClassification.from_pretrained("prithivida/parrot_fluency_model") - Notebooks
- Google Colab
- Kaggle
Commit ·
e5224ff
1
Parent(s): b4c1e28
Add TF weights (#1)
Browse files- Add TF weights (8d25697a7c3decfe5fa7fb9be4a51e1a204d3e97)
Co-authored-by: Joao Gante <joaogante@users.noreply.huggingface.co>
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:398a5f1b23a94bc5350fa2008b097f156212c7bbda7312786d64e39760b07f48
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size 438223128
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