Instructions to use Brand066/sequence_classification_sendmessage_or_rag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Brand066/sequence_classification_sendmessage_or_rag with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Brand066/sequence_classification_sendmessage_or_rag")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Brand066/sequence_classification_sendmessage_or_rag") model = AutoModelForSequenceClassification.from_pretrained("Brand066/sequence_classification_sendmessage_or_rag") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1ed7c3b226f0eefadcd0472a198161070e8b45273f173b6d067a957d88a98ba
- Size of remote file:
- 268 MB
- SHA256:
- cf2dac69345fec5ecc4bc60e1359749ad5e7b9dd3cba226035717ed274ba3936
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