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
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README.md
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## Results
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|Set|Metric| # Score|
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| Test |Rouge2 - mid -precision | ****|
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| Test | Rouge2 - mid - recall | ****|
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| Test | Rouge2 - mid - fmeasure | ****|
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## Usage
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```python
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import torch
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## Results
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|Set|Metric| # Score|
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| Test |Rouge2 - mid -precision | **33.04**|
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| Test | Rouge2 - mid - recall | **33.83**|
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| Test | Rouge2 - mid - fmeasure | **33.15**|
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## Usage
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```python
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import torch
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