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Update README.md (#3604)

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Update AutoModel & AutoTokernizer loading.
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ahotrod
2020-04-03 06:28:25 -07:00
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parent e91692f4a3
commit 1ac6a246d8
1 changed files with 2 additions and 16 deletions
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model_cards/ahotrod/xlnet_large_squad2_512/README.md
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@@ -56,22 +56,8 @@ PyTorch: 1.4.0
TensorFlow: 2.1.0 TensorFlow: 2.1.0
Python: 3.7.6 Python: 3.7.6
``` ```
### Inferencing / prediction works with Transformers v2.4.1, the latest version tested
### Utilize this xlnet_large_squad2_512 fine-tuned model with: ### Utilize this xlnet_large_squad2_512 fine-tuned model with:
```python ```python
config_class, model_class, tokenizer_class = \ tokenizer = AutoTokenizer.from_pretrained("ahotrod/xlnet_large_squad2_512")
XLNetConfig, XLNetforQuestionAnswering, XLNetTokenizer model = AutoModelForQuestionAnswering.from_pretrained("ahotrod/xlnet_large_squad2_512")
model_name_or_path = "ahotrod/xlnet_large_squad2_512"
config = config_class.from_pretrained(model_name_or_path)
tokenizer = tokenizer_class.from_pretrained(model_name_or_path, do_lower_case=True)
model = model_class.from_pretrained(model_name_or_path, config=config)
```
### or the AutoModels (AutoConfig, AutoTokenizer & AutoModel) should also work, however I have yet to use them in my apps & confirm:
```python
from transformers import AutoConfig, AutoTokenizer, AutoModel
model_name_or_path = "ahotrod/xlnet_large_squad2_512"
config = AutoConfig.from_pretrained(model_name_or_path)
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, do_lower_case=True)
model = AutoModel.from_pretrained(model_name_or_path, config=config)
``` ```