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, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("philippelaban/summary_loop10") model = AutoModelForCausalLM.from_pretrained("philippelaban/summary_loop10") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Example output
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```
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```
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# Github repo
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# Example output
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```
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[Score: -0.084] Here's what you need to know about rockfalls
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[Score: -0.087] Here's what you need to know about these tracks
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[Score: -0.091] Here's what we know so far about these tracks
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[Score: -0.101] Here's what you need to know about rockfall
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```
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# Github repo
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