---
language:
- en
license: llama2
tags:
- Xwin
- Euryale 1.3
- Platypus2
- WinterGoddess
- frankenmerge
- dare
- ties
- 90b
pipeline_tag: conversational
model-index:
- name: BigWeave-v12-90b
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 68.09
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v12-90b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 87.7
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v12-90b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 69.41
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v12-90b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 61.35
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v12-90b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 81.22
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v12-90b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 47.38
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v12-90b
      name: Open LLM Leaderboard
---
# BigWeave v12 90B

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

The BigWeave models aim to identify merge settings equaling or surpassing the performance of Goliath-120b. The version number merely tracks various attempts and is not a quality indicator. Only results demonstrating good performance are retained and shared.

This version is a DARE-TIES merge of two passthrough merges: Xwin-LM-70b-v0.1 + Euryale-1.3-70b ([BigWeave v6](https://huggingface.co/llmixer/BigWeave-v6-90b)) and Platypus2-70b-instruct + WinterGoddess-1.4x-70b (BigWeave v8). Both models individually show strong performance, and the merged model achieves even lower perplexity than each model separately.

The 90b size allows for 4bit quants to fit into 48GB of VRAM.

# Prompting Format
Vicuna and Alpaca.

# Merge process
The models used in the merge are [Xwin-LM-70b-v0.1](https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1), [Euryale-1.3-70b](https://huggingface.co/Sao10K/Euryale-1.3-L2-70B), [Platypus2-70b-instruct](https://huggingface.co/garage-bAInd/Platypus2-70B-instruct) and [WinterGoddess-1.4x-70b](https://huggingface.co/Sao10K/WinterGoddess-1.4x-70B-L2).

Merge configuration:
```
slices:
  - sources:
    - model: Xwin-LM/Xwin-LM-70B-V0.1
      layer_range: [0,12]
  - sources:
    - model: Sao10K/Euryale-1.3-L2-70B
      layer_range: [9,14]
  - sources:
    - model: Xwin-LM/Xwin-LM-70B-V0.1
      layer_range: [12,62]
  - sources:
    - model: Sao10K/Euryale-1.3-L2-70B
      layer_range: [54,71]
  - sources:
    - model: Xwin-LM/Xwin-LM-70B-V0.1
      layer_range: [62,80]
merge_method: passthrough
dtype: float16
---
slices:
  - sources:
    - model: garage-bAInd/Platypus2-70B-instruct
      layer_range: [0,12]
  - sources:
    - model: Sao10K/WinterGoddess-1.4x-70B-L2
      layer_range: [9,14]
  - sources:
    - model: garage-bAInd/Platypus2-70B-instruct
      layer_range: [12,62]
  - sources:
    - model: Sao10/WinterGoddess-1.4x-70B-L2
      layer_range: [54,71]
  - sources:
    - model: garage-bAInd/Platypus2-70B-instruct
      layer_range: [62,80]
merge_method: passthrough
dtype: float16
---
models:
    - model: llmixer/BigWeave-v8-90b
      parameters:
        weight: 0.5
        density: 0.25
merge_method: dare_ties
base_model: llmixer/BigWeave-v6-90b
dtype: float16
```

# Acknowledgements
[@Xwin-LM](https://huggingface.co/Xwin-LM) For creating Xwin

[@Sao10K](https://huggingface.co/Sao10K) For creating Euryale and WinterGoddess

[@garage-bAInd](https://huggingface.co/garage-bAInd) For creating Platypus2

[@alpindale](https://huggingface.co/alpindale) For creating the original Goliath

[@chargoddard](https://huggingface.co/chargoddard) For developing [mergekit](https://github.com/cg123/mergekit).

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_llmixer__BigWeave-v12-90b)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |69.19|
|AI2 Reasoning Challenge (25-Shot)|68.09|
|HellaSwag (10-Shot)              |87.70|
|MMLU (5-Shot)                    |69.41|
|TruthfulQA (0-shot)              |61.35|
|Winogrande (5-shot)              |81.22|
|GSM8k (5-shot)                   |47.38|