Instructions to use hf-internal-testing/tiny-random-GPT2ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPT2ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-GPT2ForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPT2ForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-GPT2ForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f73581c3eb258ac445c8d90c2e67da712a330e8003e0bf951086efd4e82b080
- Size of remote file:
- 1.65 MB
- SHA256:
- 8523a95d854d771e24351a8fb91cee46f080801562f1dc05a2aa3316e695eab3
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