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README.md
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---
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license: mit
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language:
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tags:
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- zero-shot-classification
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- text-classification
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# xlm-roberta-large-portuguese-execspeech-cap-v3
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## Model description
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An `xlm-roberta-large` model finetuned on
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## How to use the model
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#### Loading and tokenizing input data
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#### Inference using the Trainer class
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```python
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model = AutoModelForSequenceClassification.from_pretrained('poltextlab/xlm-roberta-large-portuguese-execspeech-cap-v3',
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num_labels=
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problem_type="multi_label_classification"
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training_args = TrainingArguments(
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output_dir='.',
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---
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license: mit
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language:
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- multilingual
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tags:
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- zero-shot-classification
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- text-classification
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---
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# xlm-roberta-large-portuguese-execspeech-cap-v3
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## Model description
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An `xlm-roberta-large` model finetuned on multilingual training data containing texts of the `execspeech` domain labelled with [major topic codes](https://www.comparativeagendas.net/pages/master-codebook) from the [Comparative Agendas Project](https://www.comparativeagendas.net/).
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## How to use the model
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#### Loading and tokenizing input data
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#### Inference using the Trainer class
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```python
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model = AutoModelForSequenceClassification.from_pretrained('poltextlab/xlm-roberta-large-portuguese-execspeech-cap-v3',
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num_labels=num_labels,
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problem_type="multi_label_classification",
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ignore_mismatched_sizes=True
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)
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training_args = TrainingArguments(
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output_dir='.',
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