Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
bert
financial-sentiment-analysis
sentiment-analysis
finance
Instructions to use ProsusAI/finbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProsusAI/finbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProsusAI/finbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProsusAI/finbert") model = AutoModelForSequenceClassification.from_pretrained("ProsusAI/finbert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.safetensors from ProsusAI/finbert: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/ProsusAI/finbert/resolve/refs%2Fpr%2F28/model.safetensors
- Command line
-
hf download hf://ProsusAI/finbert@refs/pr/28/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ProsusAI/finbert/resolve/refs%2Fpr%2F28/model.safetensors
438 MB
- Xet hash:
- 97c9cb12d04352c17ea4a86542c6411d19940e4418e13199087eba3230f3c144
- Size of remote file:
- 438 MB
- SHA256:
- e5897858ff819aad7629b96ce521ae5477952d03634ef5dd30ed2d76357a9f00
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