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--- |
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base_model: [] |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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license: apache-2.0 |
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--- |
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# Credit for the model card's description goes to ddh0, mergekit, and, MTSAIR |
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# multi_verse_model-10.7B |
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This is multi_verse_model-10.7B, a depth-upscaled version of [MTSAIR/multi_verse_model](https://huggingface.co/MTSAIR/multi_verse_model). |
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This model is intended to be used as a basis for further fine-tuning, or as a drop-in upgrade from the original 7 billion parameter model. |
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Paper detailing how Depth-Up Scaling works: [SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling](https://arxiv.org/abs/2312.15166) |
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). |
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## Merge Details |
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### Merge Method |
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This model was merged using the passthrough merge method. |
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### Models Merged |
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The following models were included in the merge: |
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* /Users/jsarnecki/opt/Workspace/MTSAIR/multi_verse_model |
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### Configuration |
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The following YAML configuration was used to produce this model: |
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```yaml |
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dtype: bfloat16 |
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merge_method: passthrough |
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slices: |
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- sources: |
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- layer_range: [0, 24] |
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model: /Users/jsarnecki/opt/Workspace/MTSAIR/multi_verse_model |
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- sources: |
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- layer_range: [8, 32] |
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model: /Users/jsarnecki/opt/Workspace/MTSAIR/multi_verse_model |
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``` |
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I'm an innovative concept, created through a cutting-edge training method. Picture me as a "learning bot" who's had a special upgrade. Just like how a chef perfects their recipes with new techniques, my creators have fine-tuned my "knowledge-absorption" process. I'm here to showcase the potential of this new approach, and I'm excited to test my abilities in a friendly, helpful manner. So, while I may be a product of experimentation, my purpose is to demonstrate the power of continuous learning and growth in the world of artificial intelligence. |
