mamba_finacial_phrasebank_sentiment

Mamba Finacial Headline Sentiment

Score 0.84 on accuracy for the finacial phrasebank dataset. A completely huggingface capitable implementation of sequence classification with mamba using: https://github.com/getorca/mamba_for_sequence_classification.

Inference:

from transformers import pipeline


model_path = 'winddude/mamba_finacial_phrasebank_sentiment'

classifier = pipeline("text-classification", model=model_path, trust_remote_code=True)

text = "Finnish retail software developer Aldata Solution Oyj reported a net loss of 11.7 mln euro $ 17.2 mln for 2007 versus a net profit of 2.5 mln euro $ 3.7 mln for 2006 ."

classifier(text)

gives: [{'label': 'NEGATIVE', 'score': 0.8793253302574158}]