Instructions to use Davidals/fire-image-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davidals/fire-image-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Davidals/fire-image-classifier") 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("Davidals/fire-image-classifier") model = AutoModelForImageClassification.from_pretrained("Davidals/fire-image-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 589 Bytes
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tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: fire-image-classifier
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 1.0
---
# fire-image-classifier
Universidad Católica Andrés Bello
Proyecto final de la materia de aprendizaje
David Liendo
Daniel Nuñez
Mickel Arroz
## Example Images
#### fire_images

#### non_fire_images
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