Text Classification
Transformers
PyTorch
TensorFlow
English
bert
sentiment-analysis
text-embeddings-inference
Instructions to use AndyChiang/my-test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndyChiang/my-test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AndyChiang/my-test-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AndyChiang/my-test-model") model = AutoModelForSequenceClassification.from_pretrained("AndyChiang/my-test-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1acac943848a7ba9e538dd9b546675affde1b52b3de1fa4c2f97fb7af73eaecf
- Size of remote file:
- 433 MB
- SHA256:
- 7dffc5146edb2b0d85868fc3ce6e9017c094092fb6cfa2520387d8c9ec592f56
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