Instructions to use winddude/mamba_financial_headline_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use winddude/mamba_financial_headline_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="winddude/mamba_financial_headline_sentiment")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("winddude/mamba_financial_headline_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97c7d0a4b65d28d036314be12a8030e4075b3fad05f6527c589a0fe6171f48b6
- Size of remote file:
- 5.55 GB
- SHA256:
- 5cc654feba82f819866dbef37aa45951ee862639f4efd52eebbc1f830bffe310
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