Instructions to use Mouwiya/image-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mouwiya/image-model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="Mouwiya/image-model")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Mouwiya/image-model") model = AutoModelForMultimodalLM.from_pretrained("Mouwiya/image-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d3854991ebfe7e0acb4dba7ed45c0fb86a3242dcaace5062b59d4adbf4c4c80
- Size of remote file:
- 15.4 MB
- SHA256:
- 734fe6642edf758f7c94d7d9149426b49d202fe8e7bf0bef47392489c3c0a559
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.