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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6ea993ef9e57a865cf9b2b9208ce630426dd6d7130127676ce506acf6225919
- Size of remote file:
- 1.59 MB
- SHA256:
- 7bc6d9e23f64aa8dc96a974803dc4b2d127d24f43a97c77e030007458e5aab8c
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