HiroseKoichi
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README.md
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---
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license: llama3
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library_name: transformers
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tags:
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- nsfw
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- not-for-all-audiences
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- llama-3
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- text-generation-inference
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- mergekit
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- merge
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---
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Original model: https://huggingface.co/HiroseKoichi/L3-8B-Lunar-Stheno
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# L3-8B-Lunar-Stheno
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L3-8B-Lunaris-v1 is definitely a significant improvement over L3-8B-Stheno-v3.2 in terms of situational awareness and prose, but it's not without issues: the response length can sometimes be very long, causing it to go on a rant; it tends to not take direct action, saying that it will do something but never actually doing it; and its performance outside of roleplay took a hit.
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This merge fixes all of those issues, and I'm genuinely impressed with the results. While I did use a SLERP merge to create this model, there was no blending of the models; all I did was replace L3-8B-Stheno-v3.2's weights with L3-8B-Lunaris-v1's.
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# Experimental Quants Included
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There's a full set of quants available, but half of them include an experimental quantization method, which is indicated by the prefix `f16` before the quantization level. These quants keep the embeddings and output tensors at f16, but is otherwise the same as the rest.
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The experimental variants should be higher quality than their standard equivalent, but any feedback is welcome.
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# Details
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- **License**: [llama3](https://llama.meta.com/llama3/license/)
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- **Instruct Format**: [llama-3](https://llama.meta.com/docs/model-cards-and-prompt-formats/meta-llama-3/)
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- **Context Size**: 8K
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## Models Used
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- [L3-8B-Stheno-v3.2](https://huggingface.co/Sao10K/L3-8B-Stheno-v3.2)
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- [L3-8B-Lunaris-v1](https://huggingface.co/Sao10K/L3-8B-Lunaris-v1)
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## Merge Config
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```yaml
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models:
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- model: Sao10K/L3-8B-Stheno-v3.2
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- model: Sao10K/L3-8B-Lunaris-v1
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merge_method: slerp
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base_model: Sao10K/L3-8B-Stheno-v3.2
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parameters:
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t:
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- filter: self_attn
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value: 0
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- filter: mlp
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value: 1
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- value: 0
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dtype: bfloat16
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```
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