Instructions to use thrunlab/Mistral_Sparse_pretraining_80_percent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thrunlab/Mistral_Sparse_pretraining_80_percent with Transformers:
# Load model directly from transformers import AutoTokenizer, SparseMistral tokenizer = AutoTokenizer.from_pretrained("thrunlab/Mistral_Sparse_pretraining_80_percent") model = SparseMistral.from_pretrained("thrunlab/Mistral_Sparse_pretraining_80_percent") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- README.md +1 -1
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README.md
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the openwebtext dataset.
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It achieves the following results on the evaluation set:
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## Model description
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the openwebtext dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.9177
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## Model description
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