Instructions to use ayoubkirouane/T5-4-Summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayoubkirouane/T5-4-Summarization 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="ayoubkirouane/T5-4-Summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ayoubkirouane/T5-4-Summarization") model = AutoModelForSeq2SeqLM.from_pretrained("ayoubkirouane/T5-4-Summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10d599f5e01845f9afc1b59935687cd4efb997ff11f9f5d2a0253bda414688ab
- Size of remote file:
- 892 MB
- SHA256:
- cdeda92be83311fd65671c2a55aac4d6873a7fa9ad6677f31dc93ee2d7cb4d72
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