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:
- c8f5e5d38b1a5fe3b93e61edcb87d6a2da1ccc4b6a8c444cf5f32c6e33aaa111
- Size of remote file:
- 438 MB
- SHA256:
- 3055a7df6566e86469ee6b4b5e37ebabc18c3e19a8097284e1856a7bd47348db
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