Text Classification
Transformers
PyTorch
English
roberta
Sentiment
RoBERTa
Financial Statements
Accounting
Finance
Business
ESG
CSR Reports
Financial News
Earnings Call Transcripts
Sustainability
Corporate governance
Instructions to use soleimanian/financial-roberta-large-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use soleimanian/financial-roberta-large-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="soleimanian/financial-roberta-large-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("soleimanian/financial-roberta-large-sentiment") model = AutoModelForSequenceClassification.from_pretrained("soleimanian/financial-roberta-large-sentiment", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- daf0586a7542bf747c73835c95faa084ce8235185f30b1e1b320d70f3a1ba509
- Size of remote file:
- 1.42 GB
- SHA256:
- 7b3541b7659518f118ffeb667a9386cdae3068b5c2b4d630ce74d52140465868
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