Instructions to use mbshr/urt5-base-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbshr/urt5-base-finetuned 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="mbshr/urt5-base-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mbshr/urt5-base-finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("mbshr/urt5-base-finetuned") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 610318adee85973ea818a9e015cc621b5dd7fb3f1169c8a07023f8452b9eac26
- Size of remote file:
- 1.04 GB
- SHA256:
- 89ea869006a20691f71682f9c41d852322ae92360156f9531b603e2e03a488d5
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