BigWeave-v20-110b

BigWeave v20 110b

<img src="https://cdn-uploads.huggingface.co/production/uploads/65a6db055c58475cf9e6def1/4CbbAN-X7ZWj702JrcCGH.png" width=600>

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 merge of 152334H/miqu-1-70b-sf and lizpreciatior/lzlv_70b_fp16_hf. By conducting exl2 measurements, we identify the least important layers of lzlv. These least important layers are extended with layers in-between to create longer series of consecutive layers. These slices are then inserted into miqu.

Merge configuration:

slices:
  - sources:
      - model: 152334H/miqu-1-70b-sf
        layer_range: [0, 1]
      - model: lizpreciatior/lzlv_70b_fp16_hf
        layer_range: [0, 1]
        parameters:
          weight: 0
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [1,26]
  - sources:
    - model: lizpreciatior/lzlv_70b_fp16_hf
      layer_range: [9,44]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [27,52]
  - sources:
    - model: lizpreciatior/lzlv_70b_fp16_hf
      layer_range: [45,60]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [53,79]
  - sources:
      - model: 152334H/miqu-1-70b-sf
        layer_range: [79, 80]
      - model: lizpreciatior/lzlv_70b_fp16_hf
        layer_range: [79, 80]
        parameters:
          weight: 0
merge_method: linear
parameters:
  weight: 1.0
dtype: float16
tokenizer_source: 152334H/miqu-1-70b-sf

Open LLM Leaderboard Evaluation Results

Detailed results can be found here