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README.md
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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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---
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-
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## Merge Details
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###
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* [unsloth/Mistral-Small-24B-Instruct-2501](https://huggingface.co/unsloth/Mistral-Small-24B-Instruct-2501)
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```yaml
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dtype: bfloat16
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- filter: down_proj
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value: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
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- value: 1
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```
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---
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language:
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- en
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license: apache-2.0
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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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base_model:
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- unsloth/Mistral-Small-24B-Base-2501
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- unsloth/Mistral-Small-24B-Instruct-2501
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- trashpanda-org/MS-24B-Instruct-Mullein-v0
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- trashpanda-org/Llama3-24B-Mullein-v1
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- ArliAI/Mistral-Small-24B-ArliAI-RPMax-v1.4
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- TheDrummer/Cydonia-24B-v2
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- estrogen/MS2501-24b-Ink-apollo-ep2
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- huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated
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- ToastyPigeon/ms3-roselily-rp-v2
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- PocketDoc/Dans-DangerousWinds-V1.1.1-24b
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- ReadyArt/Forgotten-Safeword-24B-V2.2
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- PocketDoc/Dans-PersonalityEngine-V1.2.0-24b
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- Undi95/MistralThinker-e2
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- lemonilia/Mistral-Small-3-Reasoner-s1
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- arcee-ai/Arcee-Blitz
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- SicariusSicariiStuff/Redemption_Wind_24B
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---
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***
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## Tantum
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>Everything is edible if you are brave enough
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### Overview
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It's kind of hard to judge a 24B model after using a 70B for a while. From some tests, I think it might be better than my ms-22B and qwen-32B merges.
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It has some prose, some character adherence, and... `<think>` tags! It will consistently think if you add `<think>` tag as prefill, tho I think it will obviously not think as well as an actual thinking model distill.
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**Settings:**
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Samplers: [Weird preset](https://files.catbox.moe/ccwmca.json) | [Mullein preset](https://files.catbox.moe/0pkv2j.json)
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Prompt format: Mistral-V7 (?)
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ChatML and Llama3 give better results imo. In the case of ChatML, there are Dans-PersonalityEngine and Redemption-Wind models that have been trained on it. But Llama3? No clue.
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I use [this](https://files.catbox.moe/daluze.json) lorebook for all chats instead of a system prompt for mistal models.
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### Quants
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[5_K_S](https://huggingface.co/Nohobby/ignore_MS3-test-Q5_K_S-GGUF/resolve/main/ignore_ms3-test-q5_k_s.gguf?download=true)
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***
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## Merge Details
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### Merging steps
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## MS3-test-Merge-1
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```yaml
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models:
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- model: unsloth/Mistral-Small-24B-Base-2501
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- model: unsloth/Mistral-Small-24B-Instruct-2501+ToastyPigeon/new-ms-rp-test-ws
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parameters:
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select_topk:
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- value: [0.05, 0.03, 0.02, 0.02, 0.01]
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- model: unsloth/Mistral-Small-24B-Instruct-2501+estrogen/MS2501-24b-Ink-ep2-adpt
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parameters:
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select_topk: 0.1
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- model: trashpanda-org/MS-24B-Instruct-Mullein-v0
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parameters:
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select_topk: 0.4
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base_model: unsloth/Mistral-Small-24B-Base-2501
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merge_method: sce
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parameters:
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int8_mask: true
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rescale: true
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normalize: true
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dtype: bfloat16
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tokenizer_source: base
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```
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```yaml
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dtype: bfloat16
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tokenizer_source: base
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merge_method: della_linear
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parameters:
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density: 0.55
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base_model: Step1
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models:
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- model: unsloth/Mistral-Small-24B-Instruct-2501
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parameters:
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weight:
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- filter: v_proj
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value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]
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- filter: o_proj
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value: [1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1]
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- filter: up_proj
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value: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
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- filter: gate_proj
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value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]
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- filter: down_proj
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value: [1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]
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- value: 0
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- model: Step1
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parameters:
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weight:
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- filter: v_proj
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value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1]
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- filter: o_proj
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value: [0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0]
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- filter: up_proj
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value: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
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- filter: gate_proj
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value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1]
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- filter: down_proj
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value: [0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1]
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- value: 1
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```
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Some early MS3 merge. Not really worth using on its own. Just added it for fun.
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## RP-half1
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```yaml
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models:
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- model: ArliAI/Mistral-Small-24B-ArliAI-RPMax-v1.4
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parameters:
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weight: 0.2
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density: 0.7
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- model: trashpanda-org/Llama3-24B-Mullein-v1
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parameters:
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weight: 0.2
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density: 0.7
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- model: TheDrummer/Cydonia-24B-v2
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parameters:
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weight: 0.2
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density: 0.7
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merge_method: della_linear
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base_model: Nohobby/MS3-test-Merge-1
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parameters:
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epsilon: 0.2
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lambda: 1.1
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dtype: bfloat16
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tokenizer:
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source: base
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```
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## RP-half2
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```yaml
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base_model: Nohobby/MS3-test-Merge-1
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parameters:
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epsilon: 0.05
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lambda: 0.9
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int8_mask: true
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rescale: true
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normalize: false
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dtype: bfloat16
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tokenizer:
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source: base
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merge_method: della
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models:
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- model: estrogen/MS2501-24b-Ink-apollo-ep2
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parameters:
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weight: [0.1, -0.01, 0.1, -0.02, 0.1]
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density: [0.6, 0.4, 0.5, 0.4, 0.6]
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- model: huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated
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parameters:
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weight: [0.02, -0.01, 0.02, -0.02, 0.01]
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density: [0.45, 0.55, 0.45, 0.55, 0.45]
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- model: ToastyPigeon/ms3-roselily-rp-v2
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parameters:
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weight: [0.01, -0.02, 0.02, -0.025, 0.01]
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density: [0.45, 0.65, 0.45, 0.65, 0.45]
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- model: PocketDoc/Dans-DangerousWinds-V1.1.1-24b
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parameters:
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weight: [0.1, -0.01, 0.1, -0.02, 0.1]
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density: [0.6, 0.4, 0.5, 0.4, 0.6]
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```
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## RP-whole
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```yaml
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base_model: ReadyArt/Forgotten-Safeword-24B-V2.2
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merge_method: model_stock
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dtype: bfloat16
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models:
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- model: mergekit-community/MS3-RP-half1
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- model: mergekit-community/MS3-RP-RP-half2
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```
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## INT
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```yaml
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merge_method: della_linear
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dtype: bfloat16
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parameters:
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normalize: true
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int8_mask: true
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tokenizer:
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source: base
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base_model: PocketDoc/Dans-PersonalityEngine-V1.2.0-24b
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models:
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- model: PocketDoc/Dans-PersonalityEngine-V1.2.0-24b
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parameters:
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density: 0.55
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weight: 1
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- model: Undi95/MistralThinker-e2
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parameters:
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density: 0.55
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weight: 1
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- model: d-rang-d/ignore_MS3-Reasoner-mergekit
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parameters:
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density: 0.55
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weight: 1
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- model: arcee-ai/Arcee-Blitz
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parameters:
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density: 0.55
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weight: 1
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```
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## Tantumv00
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```yaml
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output_base_model: "SicariusSicariiStuff/Redemption_Wind_24B"
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output_dtype: "bfloat16"
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finetune_merge:
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- { "model": "mergekit-community/MS3-INT", "base": "unsloth/Mistral-Small-24B-Instruct-2501", "alpha": 1.0, "is_input": true }
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- { "model": "mergekit-community/MS-RP-whole", "base": "unsloth/Mistral-Small-24B-Instruct-2501", "alpha": 0.7, "is_output": true }
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output_dir: "output_model"
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device: "cpu"
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clean_cache: false
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cache_dir: "cache"
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storage_dir: "storage"
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```
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Doesn't look like a mergekit recipe, right? Well, it's not. It's for a standalone merge tool: https://github.com/54rt1n/shardmerge
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If you want to use it for something non-qwen you can replace index.py with [this](https://files.catbox.moe/bgxmuz.py) and writer.py with [that](https://files.catbox.moe/ewww39.py). A much better solution is possible, ofc, but I'm a dumdum and can't code. The creator knows about this issue and will fix it... Someday, I guess.
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You also need to know that this thing is *really* slow, and it took me 5 hours to cram 3 24B models together.
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## Tantumv01
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```yaml
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dtype: bfloat16
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- filter: down_proj
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value: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
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- value: 1
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```
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