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:
- 5fc51a7379f0f6ae224496c1046e24889e940e44b66dbdeb9221ec230e5a6e66
- Size of remote file:
- 536 MB
- SHA256:
- 5619b277bff481f9a59d230787ad34b3ced4b55d730897d0c29bcc85689af966
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