Instructions to use NLPScholars/Roberta-Earning-Call-Transcript-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLPScholars/Roberta-Earning-Call-Transcript-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NLPScholars/Roberta-Earning-Call-Transcript-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NLPScholars/Roberta-Earning-Call-Transcript-Classification") model = AutoModelForSequenceClassification.from_pretrained("NLPScholars/Roberta-Earning-Call-Transcript-Classification") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 4ebcc2f
Update config.json
Browse files- config.json +1 -1
config.json
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"problem_type": "multi_label_classification",
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"transformers_version": "4.11.0",
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"type_vocab_size": 1,
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"vocab_size": 50265
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}
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"problem_type": "multi_label_classification",
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"transformers_version": "4.11.0",
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"type_vocab_size": 1,
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"vocab_size": 50265
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}
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