Text Classification
Transformers
Safetensors
English
multimodal
image-classification
distilbert
vit
gated-fusion
digital-humanities
Instructions to use xablex/prosody_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xablex/prosody_models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xablex/prosody_models")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xablex/prosody_models", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "ViTImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| } | |
| } | |