Summarization
Transformers
PyTorch
Enawené-Nawé
mt5
text2text-generation
Trained with AutoTrain
Eval Results (legacy)
Instructions to use ell-hol/mT5-OrangeSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ell-hol/mT5-OrangeSum 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="ell-hol/mT5-OrangeSum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ell-hol/mT5-OrangeSum") model = AutoModelForSeq2SeqLM.from_pretrained("ell-hol/mT5-OrangeSum") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
autoevaluator HF Staff
Add evaluation results on the abstract config and validation split of orange_sum (#1)
f3b573f