Text Classification
Transformers
PyTorch
TensorFlow
ONNX
Safetensors
distilbert
text-embeddings-inference
Instructions to use Ixa12345/classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ixa12345/classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ixa12345/classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ixa12345/classification-model") model = AutoModelForSequenceClassification.from_pretrained("Ixa12345/classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d259cbb8f8a4cf77647835d6659187d81fdbb5c16228e7cb92c356eeb01e273
- Size of remote file:
- 263 MB
- SHA256:
- 89bb1c03c52a90f666a7ef6b216c5fa07608ce4355b16dc984192f1edb08b113
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