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
Download pytorch_model.bin from bardsai/finance-sentiment-pl-base: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/bardsai/finance-sentiment-pl-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bardsai/finance-sentiment-pl-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bardsai/finance-sentiment-pl-base/resolve/main/pytorch_model.bin
498 MB
- Xet hash:
- a891949e159ec54f972d62657abdc055abfaf861b3597df06e96c774334c1167
- Size of remote file:
- 498 MB
- SHA256:
- 7d704ca408a024c5de1274cb85c5e473cfde4363ce773ac23d107efef6399cbc
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