Instructions to use bayan10/summarization-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bayan10/summarization-model 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="bayan10/summarization-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("bayan10/summarization-model") model = AutoModelForSeq2SeqLM.from_pretrained("bayan10/summarization-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 418f57d65b9ed433cb9b2396c674c2627b5ee3020ef45e02327fd28a111f521a
- Size of remote file:
- 557 MB
- SHA256:
- e0302e1fd286d585ae9c79e4c7dd49a4026be863cdcb480bd1b119e29028db20
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