Text Classification
Transformers
PyTorch
Safetensors
Chinese
bert
financial-sentiment-analysis
sentiment-analysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use bardsai/finance-sentiment-zh-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/finance-sentiment-zh-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/finance-sentiment-zh-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/finance-sentiment-zh-base") model = AutoModelForSequenceClassification.from_pretrained("bardsai/finance-sentiment-zh-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a742f5c718119f38f988d4c9fe6283051a7111e430ea73fd938d202a1d8b0af
- Size of remote file:
- 409 MB
- SHA256:
- 343d10fec860bd0038d4006ea8301383952a566f94154dea722509b77e4cb23f
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