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Meggido/
Llama-3-8B-Irene-v0.2-6.5bpw-h8-exl2

Name: Llama-3-8B-Irene-v0.2-6.5bpw-h8-exl2
Availability: InStock

⚡ExLlamaV2 quant of : Llama-3-8B-Irene-v0.2

[!note] ➡️ Exl2 version : 0.0.20
➡️ Cal. dataset : Default.
📄 Measurement.json file.

[!IMPORTANT] Quants:
mradermacher/Llama-3-8B-Irene-v0.2-GGUF
mradermacher/Llama-3-8B-Irene-v0.2-i1-GGUF

Llama-3-8B-Irene-v0.2

Mergin' o' models, ye say? Well, that be a task fit fer a clever gnome like meself! When combinin' similar models, I like to use model stock tae bring 'em together. And when I'm slerpin', I makes sure tae use a gradient that tapers off at both ends. That way, the model stays mostly uncensored, ye see.

Now, if I'm mergin' two uncensored models with Slerp, I just favors the one I want more o'! But when it comes tae makin' the gradient, I likes tae get wild and fluctuate between low and high values, ye know what I mean? It's like addin' a bit o' magic tae the mix, helps keep the results from gettin' too boring.

Course, this be just one gnome's way o' doin' things. I'm sure there be other clever methods out there

Merge Details

Merge Method

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

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Mergekit/llama3-SOVL-v1
grimjim/llama-3-merge-virt-req-8B
NousResearch/Meta-Llama-3-8B-Instruct
Locutusque/llama-3-neural-chat-v2.2-8B
NousResearch/Hermes-2-Pro-Llama-3-8B
rombodawg/Llama-3-8B-Instruct-Coder-v2
aaditya/Llama3-OpenBioLLM-8B
ResplendentAI/SOVL_Llama3_8B
openlynn/Llama-3-Soliloquy-8B-v2
grimjim/llama-3-merge-pp-instruct-8B
ChaoticNeutrals/Poppy_Porpoise-0.72-L3-8B

Configuration

The following YAML configuration was used to produce this model:

yaml

slices:
  - sources:
      - model: grimjim/llama-3-merge-virt-req-8B
        layer_range: [0, 32]
      - model: Mergekit/llama3-SOVL-v1
        layer_range: [0, 32]
merge_method: slerp
base_model: grimjim/llama-3-merge-virt-req-8B
parameters:
  t:
    - value: [0.5, 0.35, 0.55, 0.35, 0.75, 0.35, 0.90, 0.35, 0.75, 0.35, 0.55, 0.35, 0.5]
dtype: bfloat16

llama3-SOVL-v1

slices:
  - sources:
      - model: Mergekit/SMART-CODER
        layer_range: [0, 32]
      - model: ResplendentAI/SOVL_Llama3_8B
        layer_range: [0, 32]
merge_method: slerp
base_model: Mergekit/SMART-CODER
parameters:
  t:
    - value: [0.90, 0.55, 0.75, 0.35, 0.45, 0.90, 0.25, 0.90, 0.45, 0.35, 0.75, 0.55, 0.90]
dtype: bfloat16

SMART-CODER

models:
  - model: NousResearch/Meta-Llama-3-8B-Instruct
  - model: Locutusque/llama-3-neural-chat-v2.2-8B
  - model: NousResearch/Hermes-2-Pro-Llama-3-8B
  - model: rombodawg/Llama-3-8B-Instruct-Coder-v2
  - model: aaditya/Llama3-OpenBioLLM-8B
merge_method: model_stock
base_model: NousResearch/Meta-Llama-3-8B-Instruct
dtype: bfloat16

Meggido/Llama-3-8B-Irene-v0.2-6.5bpw-h8-exl2