Instructions to use Frenz/modelsent_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Frenz/modelsent_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Frenz/modelsent_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Frenz/modelsent_test") model = AutoModelForSequenceClassification.from_pretrained("Frenz/modelsent_test") - Notebooks
- Google Colab
- Kaggle
Upload 2 files
Browse filesfile quantized 8 int onnx format
- sentiment-int8.onnx +3 -0
- tokenizer_sentiment.pkl +3 -0
sentiment-int8.onnx
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oid sha256:8793001d5cbe068ffae63a1d110fb26c85e1c30a8bc9065889cf22cfffe690be
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tokenizer_sentiment.pkl
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oid sha256:ba0ce92f94f8fab046b0f33583773ed5ecd4370f15799b12a533c71b046d9138
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size 1314921
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