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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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- llama 3 |
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- 70b |
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- arimas |
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- story |
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- roleplay |
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- rp |
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--- |
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# EXL2 quants of [ryzen88_Llama-3-70b-Arimas-story-RP-V1.6](https://huggingface.co./ryzen88_Llama-3-70b-Arimas-story-RP-V1.6) |
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[3.00 bits per weight](https://huggingface.co./kim512/Llama-3-70b-Arimas-story-RP-V1.6-3.0bpw-h6-exl2) |
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[3.50 bits per weight](https://huggingface.co./kim512/Llama-3-70b-Arimas-story-RP-V1.6-3.5bpw-h6-exl2) |
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[4.00 bits per weight](https://huggingface.co./kim512/Llama-3-70b-Arimas-story-RP-V1.6-4.0bpw-h6-exl2) |
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[4.50 bits per weight](https://huggingface.co./kim512/Llama-3-70b-Arimas-story-RP-V1.6-4.5bpw-h6-exl2) |
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[6.00 bits per weight](https://huggingface.co./kim512/Llama-3-70b-Arimas-story-RP-V1.6-6.0bpw-h6-exl2) |
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[8.00 bits per weight](https://huggingface.co./kim512/Llama-3-70b-Arimas-story-RP-V1.6-8.0bpw-h8-exl2) |
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Created using the defaults from exllamav2 1.4.0 convert.py |
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3.0bpw to 6.0bpw head bits = 6 |
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8.0bpw head bits = 8 |
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length = 8192 |
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dataset rows = 200 |
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measurement rows = 32 |
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measurement length = 8192 |
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# model |
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Llama-3-70b-Arimas-story-RP-V1.6 |
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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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I Greatly expanded the amount of models used in this merge, experimented a lot with different idea's. |
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This version feels a lot more convincing than V1.5 Hopefully the long context window will also remain strong after Quants. |
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Because of the many merges switched back from BFloat to Float. |
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Tried breadcrums without the Ties, that went very poorly. |
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### Merge Method |
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This model was merged using the breadcrumbs_ties merge method using I:\Llama-3-70B-Instruct-Gradient-262k as a base. |
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### Models Merged |
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The following models were included in the merge: |
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* \Smaug-Llama-3-70B-Instruct |
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* \Meta-LLama-3-Cat-Smaug-LLama-70b |
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* \Meta-LLama-3-Cat-A-LLama-70b |
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* \Llama-3-70B-Synthia-v3.5 |
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* \Llama-3-70B-Instruct-Gradient-524k |
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* \Llama-3-70B-Instruct-Gradient-262k |
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* \Tess-2.0-Llama-3-70B-v0.2 |
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* \Llama-3-Lumimaid-70B-v0.1-alt |
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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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models: |
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- model: \Llama-3-70B-Instruct-Gradient-262k |
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parameters: |
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weight: 0.25 |
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density: 0.90 |
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gamma: 0.01 |
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- model: \Meta-LLama-3-Cat-Smaug-LLama-70b |
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parameters: |
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weight: 0.28 |
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density: 0.90 |
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gamma: 0.01 |
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- model: \Llama-3-Lumimaid-70B-v0.1-alt |
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parameters: |
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weight: 0.15 |
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density: 0.90 |
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gamma: 0.01 |
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- model: \Tess-2.0-Llama-3-70B-v0.2 |
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parameters: |
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weight: 0.06 |
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density: 0.90 |
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gamma: 0.01 |
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- model: \Smaug-Llama-3-70B-Instruct |
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parameters: |
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weight: 0.04 |
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density: 0.90 |
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gamma: 0.01 |
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- model: \Llama-3-70B-Synthia-v3.5 |
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parameters: |
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weight: 0.05 |
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density: 0.90 |
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gamma: 0.01 |
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- model: \Llama-3-70B-Instruct-Gradient-524k |
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parameters: |
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weight: 0.03 |
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density: 0.90 |
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gamma: 0.01 |
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- model: \Meta-LLama-3-Cat-A-LLama-70b |
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parameters: |
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weight: 0.14 |
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density: 0.90 |
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gamma: 0.01 |
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merge_method: breadcrumbs_ties |
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base_model: I:\Llama-3-70B-Instruct-Gradient-262k |
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dtype: float16 |
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``` |
