Instructions to use Thibalte/captionning_project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Thibalte/captionning_project 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="Thibalte/captionning_project")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Thibalte/captionning_project") model = AutoModelForMultimodalLM.from_pretrained("Thibalte/captionning_project", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 836fb94b0afedf06bf66f8710529263a5b0c8f4f0091026a6d5d8552dbce1d94
- Size of remote file:
- 957 MB
- SHA256:
- 6c418da3824337ff319cd04f40483429bd65d77b7ba96458d85fcb7d11a476e9
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