Instructions to use philippelaban/summary_loop10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philippelaban/summary_loop10 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" 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("summarization", model="philippelaban/summary_loop10")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("philippelaban/summary_loop10") model = AutoModelForMultimodalLM.from_pretrained("philippelaban/summary_loop10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f64c689d5ee19f04cda7e694d2511c349903aeb54bf717950d59814d49eebd53
- Size of remote file:
- 262 MB
- SHA256:
- 14a1ea4001bf1c9acfb590fdc2eafc08f860db0142996cf1416ed4f1753d02f0
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