Instructions to use CMacD12/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CMacD12/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CMacD12/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CMacD12/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("CMacD12/my_awesome_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3c4cf940583db4c73da72e50e8c930eaf4a9e92ef4ce38e5f6ec6963ca899f5
- Size of remote file:
- 268 MB
- SHA256:
- 4a33e0728935ca4cc1420be6cc08b5fd771dba21a4da1295efa5a08a602ad89b
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