Instructions to use xma/gptj-small-train-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xma/gptj-small-train-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xma/gptj-small-train-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xma/gptj-small-train-test") model = AutoModelForSequenceClassification.from_pretrained("xma/gptj-small-train-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91e70ea0f2191b810e5fa955f1ef6bc611f3cb379c384a45d30fa5f944de3d84
- Size of remote file:
- 2.99 kB
- SHA256:
- ae5ad28b73758506b0b7c5f7ee6ff2eb1cc0ea598fdab2f676419015db9745e3
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