Instructions to use shavirazh/my_first_emotion_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shavirazh/my_first_emotion_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="shavirazh/my_first_emotion_classification_model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("shavirazh/my_first_emotion_classification_model") model = AutoModelForImageClassification.from_pretrained("shavirazh/my_first_emotion_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9b79cbe79d433aed461361a4317f4f25d91780049caec4310af9121df620f3c
- Size of remote file:
- 5.3 kB
- SHA256:
- 939fd6f731724bb519233b88d2b70bf179b2054ee09ca61d03558b6d6b955d0e
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