Summarization
Transformers
Safetensors
mbart
text2text-generation
mbart-50
multilingual
news-summarization
xlsum
Instructions to use mskayacioglu/mbart50-xlsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mskayacioglu/mbart50-xlsum 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="mskayacioglu/mbart50-xlsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mskayacioglu/mbart50-xlsum") model = AutoModelForSeq2SeqLM.from_pretrained("mskayacioglu/mbart50-xlsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cba4bf46cae7fba109939617af23f4a1c4e7c7ad1e9d7c2dc28cb48f4493fecf
- Size of remote file:
- 17.1 MB
- SHA256:
- a5ff9b3222cbf6b2d8f7cf4c2ac0c5f7fbec0581664775862af9c026e8e8c576
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