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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b1f2b5fb95da21580c197a63c0b5b8a3b9689ac4911433c468aeb3996300a9c
- Size of remote file:
- 4.79 kB
- SHA256:
- e659d03ffe6756d57c4e0e598cf990e7f41d01544dda0051abdb26300ef89e7f
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