Instructions to use csebuetnlp/mT5_m2o_english_crossSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csebuetnlp/mT5_m2o_english_crossSum 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="csebuetnlp/mT5_m2o_english_crossSum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/mT5_m2o_english_crossSum") model = AutoModelForSeq2SeqLM.from_pretrained("csebuetnlp/mT5_m2o_english_crossSum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Update dataset YAML metadata for model
#3
by librarian-bot - opened
This is a pull request to add a dataset, csebuetnlp/CrossSum, to the metadata for your model (defined in the YAML block of your model's README.md).
The pull request was made by librarian-bot and used a combination of rules and/or machine learning to suggest this additional metadata.
If this suggestion is incorrect, feel free to close this pull request.
Librarian Bot was made by @davanstrien; feel free to get in touch with feedback.