Instructions to use Tiiny/TurboSparse-Mixtral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tiiny/TurboSparse-Mixtral with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Tiiny/TurboSparse-Mixtral", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Tiiny/TurboSparse-Mixtral", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Yixin Song commited on
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README.md
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@@ -9,7 +9,7 @@ The SuperSparse-Mixtral Large Language Model (LLM) is an sparsified version of t
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The average performance is
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## Inference
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The average performance is evaluated using benchmarks from the OpenLLM Leaderboard.
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## Inference
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