Instructions to use hf-tiny-model-private/tiny-random-OpenAIGPTForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-OpenAIGPTForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-OpenAIGPTForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-OpenAIGPTForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-OpenAIGPTForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57e9d0a224a58c83a3108efee22cce76916d3c1871c55162a3e291e45a548217
- Size of remote file:
- 584 kB
- SHA256:
- 87dffed6a14ea6721747900927996369e5ae74d141d0e215499b5da8ff408c7c
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