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Update README.md (#3603)

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ahotrod
2020-04-03 06:27:57 -07:00
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model_cards/ahotrod/albert_xxlargev1_squad2_512/README.md
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@@ -64,27 +64,8 @@ TensorFlow: 2.1.0
Python: 3.7.6 Python: 3.7.6
``` ```
### Inferencing / prediction works with the current Transformers v2.4.1 ### Access this albert_xxlargev1_sqd2_512 fine-tuned model with:
### Access this albert_xxlargev1_sqd2_512 fine-tuned model with "tried & true" code:
```python ```python
config_class, model_class, tokenizer_class = \ tokenizer = AutoTokenizer.from_pretrained("ahotrod/albert_xxlargev1_squad2_512")
AlbertConfig, AlbertForQuestionAnswering, AlbertTokenizer model = AutoModelForQuestionAnswering.from_pretrained("ahotrod/albert_xxlargev1_squad2_512")
model_name_or_path = "ahotrod/albert_xxlargev1_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 app & confirm:
```python
from transformers import AutoConfig, AutoTokenizer, AutoModel
model_name_or_path = "ahotrod/albert_xxlargev1_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)
```