Instructions to use philippelaban/summary_loop46 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philippelaban/summary_loop46 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_loop46")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("philippelaban/summary_loop46") model = AutoModelForCausalLM.from_pretrained("philippelaban/summary_loop46") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cf05b9d8c77456706673549843e37f6792f5588f9009e15dba8bacdb59e4d93
- Size of remote file:
- 262 MB
- SHA256:
- 03e9cf068c23db5589cc52c0d41eb7f1bf9e6d45d0a506c104cba5105e50c267
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