Instructions to use jorgeortizv/reviewUsefulness-multiclassClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jorgeortizv/reviewUsefulness-multiclassClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jorgeortizv/reviewUsefulness-multiclassClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jorgeortizv/reviewUsefulness-multiclassClassification") model = AutoModelForSequenceClassification.from_pretrained("jorgeortizv/reviewUsefulness-multiclassClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jorgeortizv/reviewUsefulness-multiclassClassification: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/jorgeortizv/reviewUsefulness-multiclassClassification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jorgeortizv/reviewUsefulness-multiclassClassification/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/jorgeortizv/reviewUsefulness-multiclassClassification/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- 282673033f88cad6e14034b78eaf77abe97faa036f33b2d2c6a64cc168acd4c6
- Size of remote file:
- 436 MB
- SHA256:
- e3bcc1b1679969de494b44cac38cbc446dd51951f7ef733bca259a3f6faeb7a1
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