Instructions to use jorgeortizv/reviewUsefulness-binaryClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jorgeortizv/reviewUsefulness-binaryClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jorgeortizv/reviewUsefulness-binaryClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jorgeortizv/reviewUsefulness-binaryClassification") model = AutoModelForSequenceClassification.from_pretrained("jorgeortizv/reviewUsefulness-binaryClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jorgeortizv/reviewUsefulness-binaryClassification: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/jorgeortizv/reviewUsefulness-binaryClassification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jorgeortizv/reviewUsefulness-binaryClassification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jorgeortizv/reviewUsefulness-binaryClassification/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- 0f79b6f42ef07f1fa520fb255d70e37b2b199d4918b3c482e5baf15df266956b
- Size of remote file:
- 436 MB
- SHA256:
- b7709e2855ae949a0b2fc97f77a9ca6167362fc3dd84202d02fc3328208acf61
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