Instructions to use hf-internal-testing/tiny-random-GPTJForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTJForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-GPTJForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTJForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-GPTJForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2db96b06ceabcf33015747dd44edb39e630d058ce1922864479163c833400d12
- Size of remote file:
- 470 kB
- SHA256:
- 43ad2e9b229f6b8dc200053d983eedc82a6ad08a37184da41422af1a2b1f88e4
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