Instructions to use philippelaban/summary_loop24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philippelaban/summary_loop24 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_loop24")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("philippelaban/summary_loop24") model = AutoModelForCausalLM.from_pretrained("philippelaban/summary_loop24") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00bae1758fc00fc0696ba4f27032467978c125c27bcfd283bb45db0573e18be2
- Size of remote file:
- 262 MB
- SHA256:
- 7dd91678b4bc54281ed549a43b3e4ca095ed49d5575a0022708962bd451d027e
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