Instructions to use hf-tiny-model-private/tiny-random-GPTNeoXModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-GPTNeoXModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-GPTNeoXModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-GPTNeoXModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-GPTNeoXModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcb13c34ce19eb6985cf8264b45505e56fd60dd005b859234086ec8c24c31ac2
- Size of remote file:
- 1.6 MB
- SHA256:
- c2fbff880dedff61c305ad35f03f8ddc5ea1b747655b7ad8b47c3cee5c3b543c
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