Instructions to use suredream/ml-cicd-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suredream/ml-cicd-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="suredream/ml-cicd-demo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("suredream/ml-cicd-demo") model = AutoModelForSequenceClassification.from_pretrained("suredream/ml-cicd-demo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e20a6dcba5a4032660fa3c7c3c3096830c7cdedcd56a640688d83d8fa0fce9fe
- Size of remote file:
- 5.71 kB
- SHA256:
- 793f00042968c566556cd112128a206059558e34cb0a9f6b990baacc2e07dc5e
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