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:
- 68606048042ac6ef54328e73a7d77858c6f8ba04f76290cfc3d8a5550271d7fb
- Size of remote file:
- 443 MB
- SHA256:
- 84ac824c7517d24ed4d3876ff5f8eb6ea05665fb393731ebd74b93325e254e77
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