Instructions to use emekaphilians/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emekaphilians/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emekaphilians/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emekaphilians/model_output") model = AutoModelForSequenceClassification.from_pretrained("emekaphilians/model_output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 075f423b1bb9d12a1e09e8afaa6ffada778af0e296a7c95d287d679a63999167
- Size of remote file:
- 5.2 kB
- SHA256:
- f0ad8ebe26bf9d9896e1e9e40c6e7c88cd1804764bf64655d5b34be953c29a80
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