Nyxene-v2-11B

Description

This repo contains bf16 files of Nyxene-v2-11B. It feels like with the new models, 1% is no longer needed as in the previous version. And yes, new version. Again.

Model used

• berkeley-nest/Starling-LM-7B-alpha
• openaccess-ai-collective/DPOpenHermes-7B
• fblgit/fblgit/una-cybertron-7b-v2
• chargoddard/loyal-piano-m7-cdpo

Prompt template

The best one after further testing is this one:

<|system|>
Below is an instruction that describes a task. Write a response that appropriately completes the request.
<|user|>
{prompt}
<|assistant|>

The secret sauce

loyal-piano-cybertron-11B :

slices:
  - sources:
    - model: fblgit/una-cybertron-7b-v2
      layer_range: [0, 24]
  - sources:
    - model: chargoddard/loyal-piano-m7-cdpo
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16

Starling-DPOHermes-11B :

slices:
  - sources:
    - model: berkeley-nest/Starling-LM-7B-alpha
      layer_range: [0, 24]
  - sources:
    - model: openaccess-ai-collective/DPOpenHermes-7B
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16

Nyxene-11B :

slices:
  - sources:
      - model: loyal-piano-cybertron-11B
        layer_range: [0, 48]
      - model: Starling-NeuralHermes-11B
        layer_range: [0, 48]
merge_method: slerp
base_model: loyal-piano-cybertron-11B
parameters:
  t:
    - filter: lm_head 
      value: [0.75]
    - filter: embed_tokens
      value: [0.75]
    - filter: self_attn
      value: [0.75, 0.25]
    - filter: mlp
      value:  [0.25, 0.75]
    - filter: layernorm
      value: [0.5, 0.5]
    - filter: modelnorm
      value: [0.75]
    - value: 0.5 # fallback for rest of tensors
dtype: bfloat16

I use mergekit for all the manipulation told here.

Thanks to the Undi95 for the original 11B mistral merge recipe.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here