Text Classification
Transformers
PyTorch
Safetensors
Japanese
bert
financial-sentiment-analysis
sentiment-analysis
Eval Results (legacy)
Instructions to use bardsai/finance-sentiment-ja-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/finance-sentiment-ja-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/finance-sentiment-ja-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/finance-sentiment-ja-base") model = AutoModelForSequenceClassification.from_pretrained("bardsai/finance-sentiment-ja-base") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#4
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:559ef04609d617028a378cfd5dc1ba49d34a85cf224396fafca9bac66dee4628
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size 442502140
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