Model Details
Full Model IDtimm/mobilenetv3_large_100.ra_in1k
Pipeline / Taskimage-classification
Librarytimm
Downloads (all-time)378.8K
Likes39
Last Modified1/20/2025
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/mobilenetv3_large_100.ra_in1k")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
timmpytorchsafetensorsimage-classificationtransformersdataset:imagenet-1karxiv:2110.00476arxiv:1905.02244license: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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⬇ Downloads378.8K
����� Community Likes39
🛠�� 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.