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:
- 90d1ce36102e88ea31ea3a79b5df88d7fb00a4f86f46cb9a54c27338d063242c
- Size of remote file:
- 4.28 kB
- SHA256:
- 8b8f00daa3565d7c84ebc1f334c75ae3ada2f187285ba5c7fd41eceded96accd
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