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:
- c2afcfb7c08cc903794c69c745f56aa97ee2d6de25d9f132cbe53892663a31d7
- Size of remote file:
- 438 MB
- SHA256:
- 05cecb5fe8b787470c9d8c2d45c9eb74c5bc95807719abc096e38da0b1b6459b
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