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:
- 2be0702f6a4b1240ca5cbf8397143a0352b6fb1d6149c4c580a8955cedbd512e
- Size of remote file:
- 6.03 kB
- SHA256:
- 1699536fb522d947cab51a2890bc77a34af999a64d9f13dfc8ab75212d18108a
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