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
Max summary length?
#4 opened almost 4 years ago
by
Melchior-Blank
Truncated results on some text
4
#3 opened almost 4 years ago
by
Sergej
Slightly better results than the reported results and some questions about the model
#2 opened almost 4 years ago
by
JingFan
This fine tuned model is not working
👍 3
4
#1 opened almost 4 years ago
by
SudhanshuBlaze