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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 423a130354767c8c2be6b0aaaca7e29b2e8d138f6624c5377d6f57907193599a
- Size of remote file:
- 32.2 MB
- SHA256:
- 289abb73383e9c58c4402599943e668259d501c3290137b9957a250325a75476
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