Instructions to use hf-internal-testing/tiny-random-ReformerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ReformerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-ReformerModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ReformerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ReformerModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcd99b0d6092606069a3dee7ccdd5fd9335c659c52fedc05bb09610ff33f50f6
- Size of remote file:
- 361 kB
- SHA256:
- 8986596d9d67bd66c16ee96034963217a711ff2200ca71a0b2acd9ad4e9e8a77
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