Instructions to use hf-tiny-model-private/tiny-random-XmodModel 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-XmodModel 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-XmodModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-XmodModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-XmodModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8837f651cbba75b91deb2c0d0318fd6f2c69f0c857e5a2dd3d9d8eea10bee339
- Size of remote file:
- 32.2 MB
- SHA256:
- 2aff42d3437dfce5f78a2904e2fd6d25d2a06cfb14250b5a818dd59053aa81ac
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