Instructions to use iarfmoose/bert-base-cased-qa-evaluator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iarfmoose/bert-base-cased-qa-evaluator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iarfmoose/bert-base-cased-qa-evaluator")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iarfmoose/bert-base-cased-qa-evaluator") model = AutoModelForSequenceClassification.from_pretrained("iarfmoose/bert-base-cased-qa-evaluator", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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Browse files
README.md
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@@ -8,7 +8,7 @@ The QA evaluator was originally designed to be used with the [t5-base-question-g
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The input for the QA evaluator follows the format for `BertForSequenceClassification`, but using the question and answer as the two sequences. Inputs should take the following format:
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[CLS] <question> [SEP] <answer [SEP]
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## Limitations and bias
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The input for the QA evaluator follows the format for `BertForSequenceClassification`, but using the question and answer as the two sequences. Inputs should take the following format:
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```
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[CLS] <question> [SEP] <answer> [SEP]
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```
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## Limitations and bias
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