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
Different inference results from local transformer vs inference API
#10
by logdeb - opened
I am getting two slightly different probability values when comparing inference results from the local transformer and inference API on the same sentence. I am wondering why this is happening? It only occurs for some sentences.
Moreover, the local transformer seems to select the highest probability result and return it alone compared to the API that returns a score for each label. Sometimes a score from the API is greater than 1 (have seen 9) and I am wondering why that is and am if the model is still functioning properly.
Cheers!
same issue here. I stopped using this model due to inconsistencies and lack of explanation.
