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:
- f2ddcd7337897f3a7fd17500993ac89769e7d3033d67e0b49876d926d6db8fc8
- Size of remote file:
- 4.03 kB
- SHA256:
- f3db3d96fdce4ca0bdb9bd7c0d6ced3f8f341c7491e72508b91ed3768451ca2a
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