Text Classification
Transformers
PyTorch
Safetensors
English
bert
finance
sentiment
finbert
multi-task-learning
Instructions to use pmatorras/financial-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pmatorras/financial-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pmatorras/financial-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pmatorras/financial-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("pmatorras/financial-sentiment-analysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed178fea39164841bfe60459b76bbf7072758c73dce7d0bde103df85c2643cfb
- Size of remote file:
- 438 MB
- SHA256:
- 73f6f0b9a46835bbafcb79128e60dbcc520613cf53f033d3f7bd0b465de192d8
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