Text Classification
Transformers
Safetensors
English
bert
Generated from Trainer
finance
text-embeddings-inference
Instructions to use samchain/EconoSentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samchain/EconoSentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="samchain/EconoSentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("samchain/EconoSentiment") model = AutoModelForSequenceClassification.from_pretrained("samchain/EconoSentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ba566ea21ea6a0e07bdb25203911ff606755c2594c4915fd7887c44d9d2ac5a
- Size of remote file:
- 5.3 kB
- SHA256:
- 1786daeba1081163696099b5fd9d6fec3e7a9ecc02941b1e2663ac57148a914c
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