Instructions to use juliensimon/distilbert-amazon-shoe-reviews-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use juliensimon/distilbert-amazon-shoe-reviews-quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="juliensimon/distilbert-amazon-shoe-reviews-quantized")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("juliensimon/distilbert-amazon-shoe-reviews-quantized") model = AutoModelForSequenceClassification.from_pretrained("juliensimon/distilbert-amazon-shoe-reviews-quantized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from juliensimon/distilbert-amazon-shoe-reviews-quantized: direct link, hf CLI and curl.
- Browser
- Download file 139 MB
-
https://huggingface.co/juliensimon/distilbert-amazon-shoe-reviews-quantized/resolve/main/pytorch_model.bin
- Command line
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hf download hf://juliensimon/distilbert-amazon-shoe-reviews-quantized/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/juliensimon/distilbert-amazon-shoe-reviews-quantized/resolve/main/pytorch_model.bin
139 MB
- Xet hash:
- fc246dd703ecdc8885d24c2249be9b058eb18ed92720f8f3c3e1839f3d59b64a
- Size of remote file:
- 139 MB
- SHA256:
- 2c999972e84f58d100bcb9cddb32e8fab805b2690f1430e2003196f968e6ed9b
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