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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8bf4d4447270adacf9dea258e3e4d708d7ca077aee1eb01f936af140e0e98b6
- Size of remote file:
- 438 MB
- SHA256:
- daf55ee85f1607a78c851d0e7ff6fc444b421b436cface3bf521478c22d0beb8
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