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 ·
89e9aae
1
Parent(s): 99f7d6d
Adding `safetensors` variant of this model (#2)
Browse files- Adding `safetensors` variant of this model (22676b9fbb6c2b830f932d743919112d32c75485)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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