Instructions to use hf-tiny-model-private/tiny-random-SwitchTransformersForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-SwitchTransformersForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-SwitchTransformersForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-SwitchTransformersForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c5b9cbb81c15378b0358ee243281c30e56d5cc83bfcb8a03aa17fde53d3c774
- Size of remote file:
- 4.49 MB
- SHA256:
- 414ddc8cf32046e7642316e61c0d4da09b2740035a58dd8cc9750a2cca628801
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