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
- Xet hash:
- a1cb0404900c2614618ba9f76301d351da731f08b3bbf1b21de99b1600e09f6c
- Size of remote file:
- 283 Bytes
- SHA256:
- b117610370253f52309d0663253878cd20c9674e2d87456e467e3ca7ba5ecf18
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