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:
- c3fb5478144195ab0bf46d8a3a47b24e18b0ffc12bb5fbe25d71456278461bf9
- Size of remote file:
- 1.47 kB
- SHA256:
- 25a7782285ceb81ba6230de6e1a892d9fa1bf35b7091cae64ab9fb365c92d548
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