Instructions to use hf-internal-testing/tiny-random-LiltModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LiltModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-LiltModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LiltModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-LiltModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcbe37af9a3ca6be22f7af66302d204c8cb983b6b46b747924aece4e56077e34
- Size of remote file:
- 280 kB
- SHA256:
- 22880cfc02f3cb591eff5f0bdba6c4f8d1537bfccbafdaa7f7ec48c0eba74c2d
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