llmixer/BigWeave-v16-103b

BigWeave v16 103b

The BigWeave models aim to experimentally identify merge settings for increasing model performance. The version number merely tracks various attempts and is not a quality indicator. Only results demonstrating good performance are retained and shared.

Prompting Format

Mistral, Vicuna and Alpaca.

Merge process

This is a self-merge of 152334H/miqu-1-70b-sf. By conducting exl2 measurements, we identify the most relevant layers. The layers are duplicated such that each group consists of consecutive layers with a two-layer overlap (i.e. larger groups than in v15).

Merge configuration:

slices:
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [0,11]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [9,13]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [11,15]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [13,17]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [15,23]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [21,25]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [23,49]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [47,51]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [49,53]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [51,55]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [53,57]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [55,59]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [57,61]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [59,63]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [61,65]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [63,67]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [65,69]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [67,71]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [69,73]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [71,75]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [73,80]
merge_method: passthrough
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	72.02
AI2 Reasoning Challenge (25-Shot)	65.87
HellaSwag (10-Shot)	87.61
MMLU (5-Shot)	73.22
TruthfulQA (0-shot)	63.81
Winogrande (5-shot)	80.43
GSM8k (5-shot)	61.18