Text Classification
Transformers
PyTorch
Safetensors
Polish
distilbert
financial-sentiment-analysis
sentiment-analysis
distiluse
Eval Results (legacy)
text-embeddings-inference
Instructions to use bardsai/finance-sentiment-pl-fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/finance-sentiment-pl-fast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/finance-sentiment-pl-fast")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/finance-sentiment-pl-fast") model = AutoModelForSequenceClassification.from_pretrained("bardsai/finance-sentiment-pl-fast", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from bardsai/finance-sentiment-pl-fast: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/bardsai/finance-sentiment-pl-fast/resolve/main/model.safetensors
- Command line
-
hf download hf://bardsai/finance-sentiment-pl-fast/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/bardsai/finance-sentiment-pl-fast/resolve/main/model.safetensors
541 MB
- Xet hash:
- 19bfc553c62d911773bc141817d6e4bf0036522a12cbdc5daf1e3a1df01de3a6
- Size of remote file:
- 541 MB
- SHA256:
- 722ce02111922d2933428d1cd50683c70756eeacb45cda1732ef12406b44a314
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