Model Details
Full Model IDtimm/resnet18.a1_in1k
Pipeline / Taskimage-classification
Librarytimm
Downloads (all-time)2.0M
Likes15
Last Modified1/21/2025
Author / Orgtimm
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-classification", model="timm/resnet18.a1_in1k")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
timmpytorchsafetensorsimage-classificationtransformersarxiv:2110.00476arxiv:1512.03385license:apache-2.0region:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🖼️ Task: Image Classification
This model is designed for the Image Classification task. Explore more models for this use case.
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⬇ Downloads2.0M
❤️ Community Likes15
🛠️ Requirements
- →Install: pip install timm
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.