Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Sharpaxis/FIN_BERT_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharpaxis/FIN_BERT_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sharpaxis/FIN_BERT_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sharpaxis/FIN_BERT_sentiment") model = AutoModelForSequenceClassification.from_pretrained("Sharpaxis/FIN_BERT_sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 485f20befd6ba1001849ff223a65a2460981e51e852c903ef41c8fce84b1c877
- Size of remote file:
- 5.3 kB
- SHA256:
- cf8165d3c6fdbefdc342dd5fc2112f452094c07187ecf41cb0ac7b47610f67bd
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