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--- |
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base_model: |
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- ArliAI/ArliAI-Llama-3-8B-Formax-v1.0 |
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- Sao10K/L3.1-8B-Niitama-v1.1 |
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- Sao10K/L3-8B-Tamamo-v1 |
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- Sao10K/L3-8B-Stheno-v3.3-32K |
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- Edgerunners/Lyraea-large-llama-3.1 |
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- gradientai/Llama-3-8B-Instruct-Gradient-1048k |
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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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Second (third) time's the charm. After fighting with Formax trying to increase it's max context to something that isn't 4k, spat out this merge as a result. Still maintains a |
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lot of v0.1's properties; creativity, literacy, and chattiness. Knowing everything I've learned making this, time to dive headfirst into making an L3.1 space whale. |
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I stg LLMs are testing me. |
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### Quants |
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[OG Q8 GGUF](https://huggingface.co/kromquant/L3.1-Siithamo-v0.2b-8B-Q8-GGUF) by me. |
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### Details & Recommended Settings |
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(Still testing; details subject to change) |
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Outputs a lot, pretty chatty like Stheno. Pulls some chaotic creativity from Niitama but its mellowed out with Tamamo. A little cliche writing, but it's almost endearing in a way. |
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Sticks to instructs fairly well and changes to match {user}'s input in length and verbosity at times. Well balanced in all RP uses. |
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I've tested this model to get up to 8-9k without any repitition, but idk what the true context limit of this model is yet. |
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Rec. Settings: |
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``` |
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Template: L3 |
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Temperature: 1.4 |
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Min P: 0.1 |
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Repeat Penalty: 1.05 |
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Repeat Penalty Tokens: 256 |
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``` |
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### Models Merged & Merge Theory |
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The following models were included in the merge: |
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* [Edgerunners/Lyraea-large-llama-3.1](https://huggingface.co/Edgerunners/Lyraea-large-llama-3.1) |
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* [Sao10K/L3-8B-Stheno-v3.3-32K](https://huggingface.co/Sao10K/L3-8B-Stheno-v3.3-32K) |
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* [Sao10K/L3.1-8B-Niitama-v1.1](https://huggingface.co/Sao10K/L3.1-8B-Niitama-v1.1) |
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* [Sao10K/L3-8B-Tamamo-v1](https://huggingface.co/Sao10K/L3-8B-Tamamo-v1) |
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* [ArliAI/ArliAI-Llama-3-8B-Formax-v1.0](https://huggingface.co/ArliAI/ArliAI-Llama-3-8B-Formax-v1.0) |
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* [gradientai/Llama-3-8B-Instruct-Gradient-1048k](https://huggingface.co/gradientai/Llama-3-8B-Instruct-Gradient-1048k) |
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Compared to v0.1, the siithamol3.1 part stayed the same. To 'increase' the context of Formax, just chopped of the ladder half and replaced it with a ~1M context model and that |
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seemed to do the trick (after doing a bunch of other shit, this was the simplest and easiest route). Then, changed from dare_linear to breadcrumbs for the final merge, gave a |
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better output without the hassle. Again, TIES anything didn't work nearly as well. |
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### Config |
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|
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```yaml |
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slices: |
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- sources: |
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- layer_range: [0, 16] |
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model: ArliAI/ArliAI-Llama-3-8B-Formax-v1.0 |
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- sources: |
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- layer_range: [16, 32] |
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model: gradientai/Llama-3-8B-Instruct-Gradient-1048k |
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parameters: |
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int8_mask: true |
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merge_method: passthrough |
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dtype: float32 |
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out_dtype: bfloat16 |
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name: formax.ext |
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--- |
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models: |
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- model: Sao10K/L3.1-8B-Niitama-v1.1 |
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- model: Sao10K/L3-8B-Stheno-v3.3-32K |
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- model: Sao10K/L3-8B-Tamamo-v1 |
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base_model: Edgerunners/Lyraea-large-llama-3.1 |
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parameters: |
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normalize: false |
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int8_mask: true |
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merge_method: model_stock |
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dtype: float32 |
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out_dtype: bfloat16 |
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name: siithamol3.1 |
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--- |
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models: |
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- model: siitamol3.1 |
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parameters: |
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weight: [0.5, 0.8, 0.9, 1] |
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density: 0.9 |
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gamma: 0.01 |
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- model: formax.ext |
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parameters: |
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weight: [0.5, 0.2, 0.1, 0] |
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density: 0.9 |
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gamma: 0.01 |
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base_model: siitamol3.1 |
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parameters: |
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normalize: false |
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int8_mask: true |
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merge_method: breadcrumbs |
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dtype: float32 |
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out_dtype: bfloat16 |
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``` |
