Text Classification
Transformers
PyTorch
TensorFlow
English
financial-sentiment-analysis
sentiment-analysis
Instructions to use yiyanghkust/finbert-tone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yiyanghkust/finbert-tone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yiyanghkust/finbert-tone")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("yiyanghkust/finbert-tone", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Add ONNX model format
#4
by chainyo - opened
Added model converted to ONNX format.
I'm looking to build a Space to showcase 🤗Optimum usage, and I decided to use your great model for the example. I don't have to create a duplicate repository because yours is already good! Is it possible to add the onnx format to simplify things this way?
@yiyanghkust Hi, could you review this PR, please?
I did one here: nickmuchi/quantized-optimum-finbert-tone, hope it helps