Fill-Mask
Transformers
PyTorch
English
roberta
Financial Language Modelling
financial-sentiment-analysis
Instructions to use SALT-NLP/FLANG-Roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SALT-NLP/FLANG-Roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SALT-NLP/FLANG-Roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SALT-NLP/FLANG-Roberta") model = AutoModelForMaskedLM.from_pretrained("SALT-NLP/FLANG-Roberta") - Notebooks
- Google Colab
- Kaggle
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- Financial Language Modelling
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## Dataset Summary
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- **Homepage:** https://salt-nlp.github.io/FLANG/
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language: en
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tags:
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- Financial Language Modelling
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- financial-sentiment-analysis
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- text: Stocks rallied and the British pound <mask>.
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## Dataset Summary
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- **Homepage:** https://salt-nlp.github.io/FLANG/
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