| | --- |
| | base_model: [] |
| | library_name: transformers |
| | tags: |
| | - mergekit |
| | - merge |
| | license: apache-2.0 |
| | --- |
| | |
| | # Credit for the model card's description goes to ddh0, mergekit, and, MTSAIR |
| |
|
| | # multi_verse_model-10.7B |
| |
|
| | This is multi_verse_model-10.7B, a depth-upscaled version of [MTSAIR/multi_verse_model](https://huggingface.co/MTSAIR/multi_verse_model). |
| |
|
| | 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. |
| |
|
| | 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) |
| |
|
| | This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). |
| |
|
| | ## Merge Details |
| | ### Merge Method |
| |
|
| | This model was merged using the passthrough merge method. |
| |
|
| | ### Models Merged |
| |
|
| | The following models were included in the merge: |
| | * /Users/jsarnecki/opt/Workspace/MTSAIR/multi_verse_model |
| |
|
| | ### Configuration |
| |
|
| | The following YAML configuration was used to produce this model: |
| |
|
| | ```yaml |
| | dtype: bfloat16 |
| | merge_method: passthrough |
| | slices: |
| | - sources: |
| | - layer_range: [0, 24] |
| | model: /Users/jsarnecki/opt/Workspace/MTSAIR/multi_verse_model |
| | - sources: |
| | - layer_range: [8, 32] |
| | model: /Users/jsarnecki/opt/Workspace/MTSAIR/multi_verse_model |
| | |
| | ``` |
| | 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. |
