Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
roberta
text-embeddings-inference
Instructions to use smeintadmin/image_intents with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smeintadmin/image_intents with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smeintadmin/image_intents")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smeintadmin/image_intents") model = AutoModelForSequenceClassification.from_pretrained("smeintadmin/image_intents", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59c85c54939ff2f1c6c619bdf4e8206f718f3e2f22fbe648b5fe08799042783f
- Size of remote file:
- 1.42 GB
- SHA256:
- e43cd6f658ac5d4d453169fc5e4509588c3acc013b48492521709449c0b77a7f
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