beberik/Nyxene-11B

Description

This repo contains bf16 files of Nyxene-11B. Like OmniMix but with new models.

Model used

• berkeley-nest/Starling-LM-7B-alpha
• mlabonne/NeuralHermes-2.5-Mistral-7B
• fblgit/juanako-7b-UNA
• ehartford/dolphin-2.1-mistral-7b

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

dolphin-juanako-11B :

slices:
  - sources:
    - model: fblgit/juanako-7b-UNA
      layer_range: [0, 24]
  - sources:
    - model: ehartford/dolphin-2.1-mistral-7b
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16

Starling-NeuralHermes-11B :

slices:
  - sources:
    - model: berkeley-nest/Starling-LM-7B-alpha
      layer_range: [0, 24]
  - sources:
    - model: mlabonne/NeuralHermes-2.5-Mistral-7B
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16

Nyxene-11B :

slices:
  - sources:
      - model: dolphin-juanako-11B
        layer_range: [0, 48]
      - model: Starling-NeuralHermes-11B
        layer_range: [0, 48]
merge_method: slerp
base_model: dolphin-juanako-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.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	67.72
AI2 Reasoning Challenge (25-Shot)	68.34
HellaSwag (10-Shot)	84.54
MMLU (5-Shot)	65.09
TruthfulQA (0-shot)	57.50
Winogrande (5-shot)	79.08
GSM8k (5-shot)	51.78