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:
- ff0b4b5ecab596ab22761cb27be963f1e1ec2de7a255529ce102addecb5b2c36
- Size of remote file:
- 32.3 MB
- SHA256:
- a117d44083bef0e2bd5338865abc2612a175f44536d2a9b31acd2c955ded03ed
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