Text Classification
Transformers
PyTorch
Safetensors
English
distilbert
sentiment-analysis
text-embeddings-inference
Instructions to use juliensimon/reviews-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use juliensimon/reviews-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="juliensimon/reviews-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("juliensimon/reviews-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("juliensimon/reviews-sentiment-analysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3c406189aa2425f6d9dc1cf0ce62016d233c36e324a116ebb42217094f21d20
- Size of remote file:
- 2.42 kB
- SHA256:
- b2c0741709ac0007557c025b938ecacc64159519d5626d679619f9212ad98ce8
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