Summarization
Transformers
PyTorch
JAX
Safetensors
Italian
t5
text2text-generation
text-generation-inference
Instructions to use efederici/it5-base-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efederici/it5-base-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="efederici/it5-base-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("efederici/it5-base-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("efederici/it5-base-summarization") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +0 -1
config.json
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"_name_or_path": "/content/output",
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"architectures": [
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"T5ForConditionalGeneration"
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],
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{
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"architectures": [
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"T5ForConditionalGeneration"
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],
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