Instructions to use Recompense/FoodVision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Recompense/FoodVision with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Recompense/FoodVision") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse filesAdding Space link
README.md
CHANGED
|
@@ -22,7 +22,7 @@ This model is an image classification model trained to identify different types
|
|
| 22 |
|
| 23 |
This model is a deep learning model for classifying food images into one of 101 categories from the Food101 dataset. It was trained using TensorFlow and likely employs a transfer learning approach, leveraging the features learned by a model pre-trained on a large dataset like ImageNet. The training process included the use of mixed precision for potentially faster training and reduced memory usage.
|
| 24 |
|
| 25 |
-
<h1 style="color:#FFD700; font-weight: bold;">
|
| 26 |
<p><a href="https://huggingface.co/spaces/Recompense/FoodVision" style="color:blue; font-weight:bold;">Use it here</a></p>
|
| 27 |
|
| 28 |
* **Developed by:** `Recompense` Me!
|
|
|
|
| 22 |
|
| 23 |
This model is a deep learning model for classifying food images into one of 101 categories from the Food101 dataset. It was trained using TensorFlow and likely employs a transfer learning approach, leveraging the features learned by a model pre-trained on a large dataset like ImageNet. The training process included the use of mixed precision for potentially faster training and reduced memory usage.
|
| 24 |
|
| 25 |
+
<h1 style="color:#FFD700; font-weight: bold;">⚛️ HuggingFace Space Food Vision Model</h1>
|
| 26 |
<p><a href="https://huggingface.co/spaces/Recompense/FoodVision" style="color:blue; font-weight:bold;">Use it here</a></p>
|
| 27 |
|
| 28 |
* **Developed by:** `Recompense` Me!
|