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
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README.md
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model = AutoModelForSequenceClassification.from_pretrained("NLPScholars/Roberta-Earning-Call-Transcript-Classification")
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```
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#
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*Sumit Ranjan [ sumit.ranjan819@gmail.com ]*
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model = AutoModelForSequenceClassification.from_pretrained("NLPScholars/Roberta-Earning-Call-Transcript-Classification")
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```
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# Contributors
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*Sumit Ranjan [ sumit.ranjan819@gmail.com ]*
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