Instructions to use credentek/TenaliAI-FinTech-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use credentek/TenaliAI-FinTech-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="credentek/TenaliAI-FinTech-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("credentek/TenaliAI-FinTech-v1") model = AutoModelForSequenceClassification.from_pretrained("credentek/TenaliAI-FinTech-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51e6d4e592f1db124f6756eb458158e8b2a448e9d3dd2b6c37df267497f3c9e1
- Size of remote file:
- 438 MB
- SHA256:
- a597d60488860d5a935789cad9bb650381c968f7667ff151aabeea0030e6a4b1
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