Instructions to use google/switch-base-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/switch-base-256 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/switch-base-256") model = AutoModelForSeq2SeqLM.from_pretrained("google/switch-base-256") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -49,8 +49,8 @@ As mentioned in the first few lines of the abstract :
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- **Model type:** Language model
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- **Language(s) (NLP):** English
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- **License:** Apache 2.0
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- **Related Models:** [All
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- **Original Checkpoints:** [All Original
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- **Resources for more information:**
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- [Research paper](https://arxiv.org/pdf/2101.03961.pdf)
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- [GitHub Repo](https://github.com/google-research/t5x)
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- **Model type:** Language model
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- **Language(s) (NLP):** English
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- **License:** Apache 2.0
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- **Related Models:** [All Switch Transformers Checkpoints](https://huggingface.co/models?search=switch)
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- **Original Checkpoints:** [All Original Switch Transformers Checkpoints](https://github.com/google-research/t5x/blob/main/docs/models.md#mixture-of-experts-moe-checkpoints)
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- **Resources for more information:**
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- [Research paper](https://arxiv.org/pdf/2101.03961.pdf)
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- [GitHub Repo](https://github.com/google-research/t5x)
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