Instructions to use Seungjun/image_captioner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Seungjun/image_captioner 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="Seungjun/image_captioner")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Seungjun/image_captioner", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -8,4 +8,7 @@ pipeline_tag: image-to-text
|
|
| 8 |
|
| 9 |
This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
|
| 10 |
- Library: [More Information Needed]
|
| 11 |
-
- Docs: [More Information Needed]
|
|
|
|
|
|
|
|
|
|
|
|
| 8 |
|
| 9 |
This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
|
| 10 |
- Library: [More Information Needed]
|
| 11 |
+
- Docs: [More Information Needed]
|
| 12 |
+
|
| 13 |
+
|
| 14 |
+
test commit
|