@@ -56,22 +56,8 @@ PyTorch: 1.4.0
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TensorFlow: 2.1.0
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Python: 3.7.6
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```
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### Inferencing / prediction works with Transformers v2.4.1, the latest version tested
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### Utilize this xlnet_large_squad2_512 fine-tuned model with:
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```python
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config_class, model_class, tokenizer_class = \
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XLNetConfig, XLNetforQuestionAnswering, XLNetTokenizer
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model_name_or_path = "ahotrod/xlnet_large_squad2_512"
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config = config_class.from_pretrained(model_name_or_path)
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tokenizer = tokenizer_class.from_pretrained(model_name_or_path, do_lower_case=True)
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model = model_class.from_pretrained(model_name_or_path, config=config)
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```
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### or the AutoModels (AutoConfig, AutoTokenizer & AutoModel) should also work, however I have yet to use them in my apps & confirm:
|
||||
```python
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from transformers import AutoConfig, AutoTokenizer, AutoModel
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model_name_or_path = "ahotrod/xlnet_large_squad2_512"
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config = AutoConfig.from_pretrained(model_name_or_path)
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tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, do_lower_case=True)
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model = AutoModel.from_pretrained(model_name_or_path, config=config)
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||||
tokenizer = AutoTokenizer.from_pretrained("ahotrod/xlnet_large_squad2_512")
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||||
model = AutoModelForQuestionAnswering.from_pretrained("ahotrod/xlnet_large_squad2_512")
|
||||
```
|
||||
|
||||
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