Instructions to use ExponentialScience/LedgerBERT-Market-Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ExponentialScience/LedgerBERT-Market-Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ExponentialScience/LedgerBERT-Market-Sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ExponentialScience/LedgerBERT-Market-Sentiment") model = AutoModelForSequenceClassification.from_pretrained("ExponentialScience/LedgerBERT-Market-Sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf3900feb779052ba89351076c5e458ce7b66621668a97c7fb624b1d1aa9669b
- Size of remote file:
- 880 MB
- SHA256:
- 61946416c1e29c5a7f5dd0f208ed57436c9c1e216adba3289f6ff1a3a236e08d
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