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 model.safetensors from ErphanRajai/yelp-polarity-roberta: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/ErphanRajai/yelp-polarity-roberta/resolve/main/model.safetensors
- Command line
-
hf download hf://ErphanRajai/yelp-polarity-roberta/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ErphanRajai/yelp-polarity-roberta/resolve/main/model.safetensors
499 MB
- Xet hash:
- 0dc41f3829d4387eb02c6b57396dc109371d80f3bafc1b9b5875f882ee247ff5
- Size of remote file:
- 499 MB
- SHA256:
- 8b61146f42dd0947276a5bfc5c50de2b564c954789234bc5a8e19e08128542cf
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