Instructions to use hf-tiny-model-private/tiny-random-GPTNeoModel 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-GPTNeoModel 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-GPTNeoModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-GPTNeoModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-GPTNeoModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84c3c77c1ab4d1474054f847ce4a752910075d9610122f6e215becda5d29313b
- Size of remote file:
- 1.47 MB
- SHA256:
- 3f2caa55b7a2a95ee5d5162598b77b9e1fad89d225f6ea2f6b39113d49894c06
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