Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Ethan615/try with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ethan615/try with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ethan615/try")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ethan615/try") model = AutoModelForSequenceClassification.from_pretrained("Ethan615/try") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 591ce30188f26301d6f3c70d6eae450c6cbc0cc95b288dbdc1bf9a1ded9b76bb
- Size of remote file:
- 536 MB
- SHA256:
- ac8cd24435eccd2b4ca297f38cac18ae9cd7ff2afe66e297614c82da9d1f8736
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