Instructions to use hf-internal-testing/tiny-random-SwitchTransformersForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SwitchTransformersForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SwitchTransformersForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-SwitchTransformersForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c37b0566839b6749f95d93015c1f34284270c1594f563b60876354379042c7c
- Size of remote file:
- 4.49 MB
- SHA256:
- b4640694949c4cebc803cf579bb888316358206848df00d9009236106647e0e8
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