Instructions to use pin/analytical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pin/analytical with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pin/analytical")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pin/analytical") model = AutoModelForSequenceClassification.from_pretrained("pin/analytical") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 404471a0020ba7289a41aefd07ce2487020bb32d936350f72484607d85b2424f
- Size of remote file:
- 442 MB
- SHA256:
- 6557782ee9e471b164ca529bf159e8ca9391b9969871d26acf5e48419973b197
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