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
File size: 302 Bytes
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license: openrail
datasets:
- smeintadmin/image_intents
language:
- en
library_name: transformers
---
Image data intents model to help classify text into either an image intent, or not an image intent. An image intent is classified as text that is asking for an image or an image to be generated. |