Instructions to use prithivida/parrot_adequacy_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivida/parrot_adequacy_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prithivida/parrot_adequacy_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prithivida/parrot_adequacy_model") model = AutoModelForSequenceClassification.from_pretrained("prithivida/parrot_adequacy_model", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from prithivida/parrot_adequacy_model: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/prithivida/parrot_adequacy_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://prithivida/parrot_adequacy_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/prithivida/parrot_adequacy_model/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- ae82bed179d8f8948c07bd22347b086a1c0a52916327bbc1f5ed8944b45ea18a
- Size of remote file:
- 1.42 GB
- SHA256:
- 4c99d7fdfbf51572c85ea422da81b86292270038f46b1c3e731b71cf8bed0f19
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