Text Classification
Transformers
PyTorch
Safetensors
Polish
bert
financial-sentiment-analysis
sentiment-analysis
herbert
Eval Results (legacy)
text-embeddings-inference
Instructions to use bardsai/finance-sentiment-pl-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/finance-sentiment-pl-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/finance-sentiment-pl-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/finance-sentiment-pl-base") model = AutoModelForSequenceClassification.from_pretrained("bardsai/finance-sentiment-pl-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 CC BY 4.0 license (inherited from HerBERT), base_model + metadata per HF guidelines
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (3c79f591847cff883f2f26c2ecb7a32597e50c39) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>6df38d1
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initial commit
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