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:
- f1d41694dc34a94f05b982c6744fca298b3927b8fdf7e6a6da8a77008931fdc1
- Size of remote file:
- 4.79 kB
- SHA256:
- ff0b8762417b71e573ee14cf5d6c55e801af11f299848bcf4bde51f1e4499d53
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