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Update README.md
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README.md
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@@ -283,6 +283,7 @@ For highest performance (but less speed), I recommend using https://huggingface.
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### How to use the model
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#### Simple zero-shot classification pipeline
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```python
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from transformers import pipeline
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classifier = pipeline("zero-shot-classification", model="MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli")
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sequence_to_classify = "Angela Merkel is a politician in Germany and leader of the CDU"
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@@ -344,6 +345,8 @@ If you have questions or ideas for cooperation, contact me at m{dot}laurer{at}vu
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### Debugging and issues
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Note that DeBERTa-v3 was released on 06.12.21 and older versions of HF Transformers seem to have issues running the model (e.g. resulting in an issue with the tokenizer). Using Transformers>=4.13 might solve some issues.
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## Model Recycling
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### How to use the model
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#### Simple zero-shot classification pipeline
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```python
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#!pip install transformers[sentencepiece]
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from transformers import pipeline
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classifier = pipeline("zero-shot-classification", model="MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli")
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sequence_to_classify = "Angela Merkel is a politician in Germany and leader of the CDU"
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### Debugging and issues
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Note that DeBERTa-v3 was released on 06.12.21 and older versions of HF Transformers seem to have issues running the model (e.g. resulting in an issue with the tokenizer). Using Transformers>=4.13 might solve some issues.
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Also make sure to install sentencepiece to avoid tokenizer errors. Run: `pip install transformers[sentencepiece]` or `pip install sentencepiece`
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## Model Recycling
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