Text Classification
Transformers
TensorFlow
English
distilbert
text classification
transformer
sentiment analysis
TensorFlow
text-embeddings-inference
Instructions to use dancingninjas/sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dancingninjas/sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dancingninjas/sentiment-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dancingninjas/sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("dancingninjas/sentiment-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66eeaa887faa839af62bcfdfd32dbd594d0d66c3977dd6f81ab24fa82d34ca56
- Size of remote file:
- 797 MB
- SHA256:
- b430c004bccb6d60904531b5392019dd6b842e6684f31f56fc3a6ddcb4ff4a8f
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