Instructions to use hf-tiny-model-private/tiny-random-YosoModel 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-YosoModel 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-YosoModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-YosoModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-YosoModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cda4d165e1849a3808416f49e65d7c40a1b12546f62f9819139ba84ad2699a05
- Size of remote file:
- 348 kB
- SHA256:
- 4159319eb7613cd67a852ccc7c033c0fa0bc3e23418c6b814e4985ac0b0e3f54
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