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--- |
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base_model: |
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- Sao10K/L3-8B-Lunaris-v1 |
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- Sao10K/L3-8B-Stheno-v3.2 |
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- Sao10K/L3-8B-Niitama-v1 |
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- Sao10K/L3-8B-Tamamo-v1 |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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quantized_by: Meggido |
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tags: |
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- merge |
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- mergekit |
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--- |
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# ⚡ExLlamaV2 quant of : [L3-SAO-MIX-8B-V1](https://huggingface.co/bluuwhale/L3-SAO-MIX-8B-V1) |
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> [!note] |
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> ➡️ **Exl2 version :** [0.2.3](https://github.com/turboderp/exllamav2/releases/tag/v0.2.3)<br/> |
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> ➡️ **Cal. dataset :** Default.<br/> |
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> 📄 <a href="https://huggingface.co/Meggido/L3-SAO-MIX-8B-V1-6.5bpw-h8-exl2/resolve/main/measurement.json" download>Measurement.json</a> file. |
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![Bluuwhale](https://huggingface.co/bluuwhale/test1/resolve/main/bluuwhale.png) |
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*** |
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# Experimental merge of [Sao10k](https://huggingface.co/Sao10K) Llama3-8B based model |
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*** |
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# L3-SAO-MIX-8B-V1 |
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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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I'm trying to combine the best model from Sao10k. And turn out, this is beyond my expectation. I use it for RP and ERP on scenario card. And it follow the instruction very well (At least for me). All credits and thanks go to Sao10k for providing amazing models used in the merge. |
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## Prompt template: Llama3 Instruct. |
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``` |
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<|begin_of_text|><|start_header_id|>system<|end_header_id|> |
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{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|> |
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{input}<|eot_id|><|start_header_id|>assistant<|end_header_id|> |
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{output}<|eot_id|> |
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``` |
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### Settings |
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``` |
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Temprature: 1.3 |
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Min-P: 0.1 |
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// If using DRY |
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Multiplier: 2 |
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Base: 1.75 |
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Allowed Length: 2 |
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Penalty Range: 0 |
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``` |
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*** |
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<details> |
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<summary><h1>Merge details</h1></summary> |
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#### Merge Method |
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This model was merged using the della merge method using Sao10K/L3-8B-Niitama-v1 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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* Sao10K/L3-8B-Lunaris-v1 |
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* Sao10K/L3-8B-Stheno-v3.2 |
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* Sao10K/L3-8B-Niitama-v1 |
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* Sao10K/L3-8B-Tamamo-v1 |
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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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base_model: Sao10K/L3-8B-Niitama-v1 |
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merge_method: della |
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dtype: bfloat16 |
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models: |
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- model: Sao10K/L3-8B-Lunaris-v1 |
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parameters: |
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weight: 1.0 |
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- model: Sao10K/L3-8B-Stheno-v3.2 |
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parameters: |
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weight: 1.0 |
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- model: Sao10K/L3-8B-Niitama-v1 |
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parameters: |
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weight: 1.0 |
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- model: Sao10K/L3-8B-Tamamo-v1 |
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parameters: |
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weight: 1.0 |
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``` |
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</details> |