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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yiyanghkust/finbert-tone: direct link, hf CLI and curl.
- Browser
- Download file 439 MB
-
https://huggingface.co/yiyanghkust/finbert-tone/resolve/refs%2Fpr%2F14/pytorch_model.bin
- Command line
-
hf download hf://yiyanghkust/finbert-tone@refs/pr/14/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yiyanghkust/finbert-tone/resolve/refs%2Fpr%2F14/pytorch_model.bin
439 MB
- Xet hash:
- 28e21fbd63982f3c26a5ece6ad938c8d25704245f46895b64bc04e9803096da6
- Size of remote file:
- 439 MB
- SHA256:
- f31c2036e91c9854bcc35141d16669dd07b9726adfe391d1011bff1de7ea4b32
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