Text Generation
Safetensors
mistral
Merge
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - Epiculous/SynthRP-Gens-v1-Filtered-n-Cleaned
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+ - Epiculous/Synthstruct-Gens-v1-Filtered-n-Cleaned
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+ language:
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+ - en
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+ - fr
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+ - de
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+ - es
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+ - it
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+ - pt
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+ - ru
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+ - zh
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+ - ja
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+ pipeline_tag: text-generation
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+ tags:
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+ - merge
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+ ---
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64adfd277b5ff762771e4571/oTCM28M_Hu6lM4DmOp7tC.png)
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+
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+ Now for something a bit different, Violet_Twilight! This model is a SLERP merge of Azure_Dusk and Crimson_Dawn!
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+
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+ # Quants!
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+ <strong>full</strong> / [exl2](https://huggingface.co/Epiculous/Azure_Dusk-v0.1-Exl2) / [gguf](https://huggingface.co/Epiculous/Azure_Dusk-v0.1-GGUF)
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+
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+ ## Prompting
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+ Violet_Twilight's models were trained with the Mistral Instruct template, therefore it should be prompted in a similar way that you would prompt any other mistral based model.
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+
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+ ```
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+ "<s>[INST] Prompt goes here [/INST]<\s>"
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+ ```
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+ ### Context and Instruct
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+ [Magnum-123B-Context.json](https://files.catbox.moe/rkyqwg.json) <br/>
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+ [Magnum-123B-Instruct.json](https://files.catbox.moe/obb5oe.json) <br/>
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+ *** NOTE *** <br/>
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+ There have been reports of the quantized model misbehaving with the mistral prompt, if you are seeing issues it may be worth trying ChatML Context and Instruct templates.
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+ If you are using GGUF I strongly advise using ChatML, for some reason that quantization performs better using ChatML.
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+ ### Current Top Sampler Settings
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+ [Crimson_Dawn-Nitral-Special](https://files.catbox.moe/8xjxht.json) - Considered the best settings! <br/>
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+ [Crimson_Dawn-Magnum-Style](https://files.catbox.moe/lc59dn.json)
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+
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+ ## Merging
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+ The following config was used to merge Azure Dusk and Crimson Dawn
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+ ```yaml
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+ slices:
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+ - sources:
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+ - model: Epiculous/Azure_Dusk-v0.1
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+ layer_range: [0, 40]
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+ - model: Epiculous/Crimson_Dawn-V0.1
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+ layer_range: [0, 40]
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+ merge_method: slerp
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+ base_model: Epiculous/Azure_Dusk-v0.1
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+ parameters:
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+ t:
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+ - filter: self_attn
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+ value: [0, 0.5, 0.3, 0.7, 1]
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+ - filter: mlp
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+ value: [1, 0.5, 0.7, 0.3, 0]
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+ - value: 0.5 # fallback for rest of tensors
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+ dtype: bfloat16
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+
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+ ```