---

base_model:

• TheDrummer/Anubis-70B-v1
• EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
• meta-llama/Llama-3.3-70B-Instruct
• Sao10K/70B-L3.3-Cirrus-x1
• SicariusSicariiStuff/Negative_LLAMA_70B
• Sao10K/L3.1-70B-Hanami-x1 library_name: transformers tags:
• mergekit
• merge license: llama3.3

---

Fixed Version

Of all my findings in the Progenitor series, this is the culmination of all the best settings. I fixed the typo I had earlier where it wasn't computing in float32, but 6 models in computed in float32 is a bit taxing on resources and time and so I left it for the configuration I thought was the best (it's not something I can afford to do with every model I make, just the worthwhile ones). This one also uses the Sicari's tokenizer which I find the best.

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the Linear DELLA merge method using nbeerbower/Llama-3.1-Nemotron-lorablated-70B as a base.

Models Merged

The following models were included in the merge:

• TheDrummer/Anubis-70B-v1
• EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
• Sao10K/70B-L3.3-Cirrus-x1
• SicariusSicariiStuff/Negative_LLAMA_70B
• Sao10K/L3.1-70B-Hanami-x1

Configuration

The following YAML configuration was used to produce this model:

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: nbeerbower/Llama-3.1-Nemotron-lorablated-70B
parameters:
  epsilon: 0.2
  lambda: 1.1
dtype: float32
out_dtype: bfloat16
tokenizer:
 source: SicariusSicariiStuff/Negative_LLAMA_70B