Text Classification
Transformers
TensorBoard
Safetensors
roberta
yelp
sentiment-analysis
polarity
Eval Results (legacy)
text-embeddings-inference
Instructions to use ErphanRajai/yelp-polarity-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ErphanRajai/yelp-polarity-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ErphanRajai/yelp-polarity-roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ErphanRajai/yelp-polarity-roberta") model = AutoModelForSequenceClassification.from_pretrained("ErphanRajai/yelp-polarity-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ErphanRajai/yelp-polarity-roberta: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/ErphanRajai/yelp-polarity-roberta/resolve/main/training_args.bin
- Command line
-
hf download hf://ErphanRajai/yelp-polarity-roberta/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ErphanRajai/yelp-polarity-roberta/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 0056c22231d0c67986bb5d55220d2d64ae61ae28133c5186775b2cc10978a96d
- Size of remote file:
- 5.78 kB
- SHA256:
- be0bbe593dcc52b3991d1c7de649a952035775ce94f7bb6bc3e93384d49eba29
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