Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use abdobilla/hcb-ai-bot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdobilla/hcb-ai-bot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="abdobilla/hcb-ai-bot") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("abdobilla/hcb-ai-bot") model = AutoModelForImageClassification.from_pretrained("abdobilla/hcb-ai-bot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
hcb-ai-bot
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
hair color 1
hair color 18
hair color 18A
hair color 1B
hair color 2
hair color 2AT P18A-1001
hair color 2B
hair color 5AT P18A-60A
hair color 5AT60A
hair color 6
hair color 60A
hair color 613
hair color 8
hair color 8T8-18
hair color 99J
hair color ASH BLONDE
hair color P10-16-613
hair color P10-22-613
hair color P18-22
hair color P18-60
hair color P2-6
hair color P27-613
hair color P2B-1B
hair color P4-18
hair color P4-8
hair color P613-14
hair color P8-22
hair color P8-613
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Evaluation results
- Accuracyself-reported0.065



























