metadata
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
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) 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, Euryale-1.3-70b, Platypus2-70b-instruct and WinterGoddess-1.4x-70b.
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|