Instructions to use csebuetnlp/mT5_m2m_crossSum_enhanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csebuetnlp/mT5_m2m_crossSum_enhanced 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_m2m_crossSum_enhanced")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/mT5_m2m_crossSum_enhanced") model = AutoModelForSeq2SeqLM.from_pretrained("csebuetnlp/mT5_m2m_crossSum_enhanced") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
91041ad | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:3acf5b79dbb88238c554c713af691cd0e7355c1db19a3b168462e318fb186a7b
size 2329707353
|