Text Classification
Transformers
PyTorch
Safetensors
German
bert
financial-sentiment-analysis
sentiment-analysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use bardsai/finance-sentiment-de-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/finance-sentiment-de-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/finance-sentiment-de-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/finance-sentiment-de-base") model = AutoModelForSequenceClassification.from_pretrained("bardsai/finance-sentiment-de-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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docs: fix year typo (20014 -> 2014) in Malo et al. citation
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docs: add MIT license (inherited from bert-base-german-cased), base_model + metadata per HF guidelines
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Update README.md
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