Instructions to use mrm8488/bert2bert_shared-german-finetuned-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert2bert_shared-german-finetuned-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="mrm8488/bert2bert_shared-german-finetuned-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert2bert_shared-german-finetuned-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/bert2bert_shared-german-finetuned-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c80de20840fa9a2821bdd4f39b6e72aa5401803df63f56cbd2b38885c2a3750e
- Size of remote file:
- 552 MB
- SHA256:
- b33b1f4db603e8a8d34e77cf34895fe336ce43e7ea30c18ad6047ddbc7909209
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