# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("sasha/autotrain-sea-slug-similarity-2498977005", device_map="auto")Quick Links
Configuration Parsing Warning:Config file config.json cannot be fetched (too big)
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2498977005
- CO2 Emissions (in grams): 13.7591
Validation Metrics
- Loss: 0.757
- Accuracy: 0.837
- Macro F1: 0.778
- Micro F1: 0.837
- Weighted F1: 0.816
- Macro Precision: 0.787
- Micro Precision: 0.837
- Weighted Precision: 0.825
- Macro Recall: 0.796
- Micro Recall: 0.837
- Weighted Recall: 0.837
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sasha/autotrain-sea-slug-similarity-2498977005") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")