Sioood/autotrain-5p0gn-ogp1m
By Sioood · ↓ 2 · ♥ 0 · Updated 2025-12-29
What's in this repo
This page lists the files in Sioood/autotrain-5p0gn-ogp1m, including model.onnx, model_bnb4.onnx, model_fp16.onnx and more.
- 8 ONNX models (.onnx files)
- 25 files, including 8 .onnx, 6 .json, 2 .safetensors, 2 .pt, 2 .bin, 1 .md
- Last updated 2025-12-29
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/model.onnx | — | Download |
| onnx/model_bnb4.onnx | — | Download |
| onnx/model_fp16.onnx | — | Download |
| onnx/model_int8.onnx | — | Download |
| onnx/model_q4.onnx | — | Download |
| onnx/model_q4f16.onnx | — | Download |
| onnx/model_quantized.onnx | — | Download |
| onnx/model_uint8.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
autotrain-5p0gn-ogp1m (ONNX)
This is an ONNX version of Sioood/autotrain-5p0gn-ogp1m. It was automatically converted and uploaded using this Hugging Face Space.
Usage with Transformers.js
See the pipeline documentation for image-classification: https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ImageClassificationPipeline
tags:
- autotrain
- transformers
- image-classification base_model: google/vit-base-patch16-224 widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg example_title: Teapot
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg example_title: Palace
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metrics
loss: 1.5330201387405396
f1_macro: 0.4888888888888888
f1_micro: 0.5416666666666666
f1_weighted: 0.5333333333333333
precision_macro: 0.5685185185185185
precision_micro: 0.5416666666666666
precision_weighted: 0.6375
recall_macro: 0.537037037037037
recall_micro: 0.5416666666666666
recall_weighted: 0.5416666666666666
accuracy: 0.5416666666666666
Model info
Created: 2025-12-29
Updated: 2025-12-29
View on Hugging Face