Instructions to use hf-internal-testing/tiny-random-XmodModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XmodModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-XmodModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XmodModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-XmodModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a387f80ee2e19d9447bc934f8ff8a9201b96920a56a448b4eee46ae751aa0ca
- Size of remote file:
- 32.3 MB
- SHA256:
- 59ace237b7446018c8c6b3580daa49a8bab0354ec01c748866ac27911bd95963
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