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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65eb0f45e246e04d8939e5f6a81019380d084ad526d1ebdd4210815652e5d92e
- Size of remote file:
- 438 MB
- SHA256:
- c7c8e85130504bc9cea3a833425bf91b6a40fdaea5197376d784eeeef65f11cf
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