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---
base_model:
- Sao10K/70B-L3.3-Cirrus-x1
- huihui-ai/Llama-3.3-70B-Instruct-abliterated
- SicariusSicariiStuff/Negative_LLAMA_70B
- TheDrummer/Anubis-70B-v1
- EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
- Sao10K/L3.1-70B-Hanami-x1
library_name: transformers
tags:
- mergekit
- merge
license: llama3.3
---
More experimentation, for this one I kept the winning formula from Progenitor V1.1 however I changed the base model to the huihui-ai/Llama-3.3-70B-Instruct-abliterated in hopes that its ability to follow instructions and its generally increased IQ would take Progenitor to the next level.
# merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Linear DELLA](https://arxiv.org/abs/2406.11617) merge method using [huihui-ai/Llama-3.3-70B-Instruct-abliterated](https://huggingface.co/huihui-ai/Llama-3.3-70B-Instruct-abliterated) as a base.
### Models Merged
The following models were included in the merge:
* [Sao10K/70B-L3.3-Cirrus-x1](https://huggingface.co/Sao10K/70B-L3.3-Cirrus-x1)
* [SicariusSicariiStuff/Negative_LLAMA_70B](https://huggingface.co/SicariusSicariiStuff/Negative_LLAMA_70B)
* [TheDrummer/Anubis-70B-v1](https://huggingface.co/TheDrummer/Anubis-70B-v1)
* [EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1](https://huggingface.co/EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1)
* [Sao10K/L3.1-70B-Hanami-x1](https://huggingface.co/Sao10K/L3.1-70B-Hanami-x1)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: Sao10K/L3.1-70B-Hanami-x1
parameters:
weight: 0.20
density: 0.7
- model: Sao10K/70B-L3.3-Cirrus-x1
parameters:
weight: 0.20
density: 0.7
- model: SicariusSicariiStuff/Negative_LLAMA_70B
parameters:
weight: 0.20
density: 0.7
- model: TheDrummer/Anubis-70B-v1
parameters:
weight: 0.20
density: 0.7
- model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
parameters:
weight: 0.20
density: 0.7
merge_method: della_linear
base_model: huihui-ai/Llama-3.3-70B-Instruct-abliterated
parameters:
epsilon: 0.2
lambda: 1.1
dype: float32
out_dtype: bfloat16
tokenizer:
source: union
```
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