Instructions to use aayumin/text_classifier_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aayumin/text_classifier_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aayumin/text_classifier_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aayumin/text_classifier_sentiment") model = AutoModelForSequenceClassification.from_pretrained("aayumin/text_classifier_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc0241e7965afbdb645b7950b0fecaa271197114eaccf386f24ca7e361520eab
- Size of remote file:
- 70.2 MB
- SHA256:
- 6d13e3381b5a1fe5233d2bbb0cea0b7f4b31a503111008796dff35596e93295b
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