Text Classification
Transformers
Safetensors
English
roberta
economics
finance
bert
language-model
financial-nlp
economic-analysis
Instructions to use beethogedeon/SentEconBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beethogedeon/SentEconBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="beethogedeon/SentEconBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("beethogedeon/SentEconBert") model = AutoModelForSequenceClassification.from_pretrained("beethogedeon/SentEconBert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e5ad62ece47d25002930bf6fc348cf19e5099494ff92bbdbbd19b37f6d707f2
- Size of remote file:
- 5.78 kB
- SHA256:
- 44cd870304227b0da5799f8287b82b4ed35672e69fd95ec741a0ed5ff2c8288c
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