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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ExponentialScience/LedgerBERT-Market-Sentiment") model = AutoModelForSequenceClassification.from_pretrained("ExponentialScience/LedgerBERT-Market-Sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Add metadata for license, library, and pipeline tag and add paper/code links (#1)
- Add metadata for license, library, and pipeline tag and add paper/code links (bb76569c0699ad9d4110a6553ec37ef206cfc696) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>5daffda
-
Added citation to preprint
Verified signature604b31b
-
Added Model Card
Verified signature4ae6f60 -
Upload folder using huggingface_hub
Verified signature4f96a1e -
initial commit
Verified signaturec50113e