Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use MarcorpAI/bert-base-uncased-banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarcorpAI/bert-base-uncased-banking77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MarcorpAI/bert-base-uncased-banking77")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MarcorpAI/bert-base-uncased-banking77") model = AutoModelForSequenceClassification.from_pretrained("MarcorpAI/bert-base-uncased-banking77") - Notebooks
- Google Colab
- Kaggle
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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## Model description
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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## Model description
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crafted a specialized model by fine-tuning BERT base uncased with the Banking77 dataset, enhancing its ability to understand and process banking-related information. This fine-tuned model is optimized for tasks within the financial domain, showcasing improved performance in tasks like sentiment analysis, intent detection, or document classification related to banking data.
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More information needed
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