Instructions to use hf-internal-testing/tiny-random-GPTNeoForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTNeoForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-GPTNeoForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTNeoForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-GPTNeoForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e3c087a568a849a9192e7f3974d58333b4e45f17e4214e87db2bbd001ccef83
- Size of remote file:
- 1.45 MB
- SHA256:
- 2c4e3bb1815ae975b0816aedcb53846ab8920a271c78a10814ffe0de7384c23d
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