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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78dbc6f686a78d322cbb518a54b2be9d173ba10cd6977fee3db6bb5f05855e5e
- Size of remote file:
- 1.7 MB
- SHA256:
- a70d377d0223bdb1b3069770e7df3e7f419517cb56ce80e26897e8368d2b341d
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