license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- openchat/openchat-3.5-0106
- machinists/Mistral-7B-SQL
model-index:
- name: haLLAwa3
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: 67.83
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLAwa3
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: 87.02
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLAwa3
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: 64.23
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLAwa3
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: 63.71
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLAwa3
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: 80.51
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLAwa3
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: 64.75
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLAwa3
name: Open LLM Leaderboard
Hallawa3: The Fusion of Expertise and Precision for 7B Models"
Unveiling 'Hallawa', an AI marvel that embodies the perfect blend of expert knowledge and cutting-edge technology, tailored for 7B models where direct answers are paramount. This AI powerhouse excels in delivering precise responses, ideal for use cases that demand accuracy and immediacy. Excelling in document understanding and prompts in its size. With 'Hallawa', you tap into a repository of intelligence that's been acknowledged by over 1400 downloads on the OpenLLM leaderboard, boasting a remarkable score of 71. This model isn't just about quantity but quality, setting new benchmarks in the realm of language models.
Whether you're looking to enhance customer service, drive research, or accelerate decision-making, 'Hallawa' stands as your go-to solution, engineered to exceed expectations in scenarios where only the most accurate and immediate answers will suffice. Join the ranks of those leveraging 'Hallawa' for their most critical applications and witness the transformation it brings to your operations. haLLAwa3 is a merge of the following models using mergekit:
🧩 Configuration
slices:
- sources:
- model: openchat/openchat-3.5-0106
layer_range: [0, 32]
- model: machinists/Mistral-7B-SQL
layer_range: [0, 32]
merge_method: slerp
base_model: openchat/openchat-3.5-0106
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 71.34 |
| AI2 Reasoning Challenge (25-Shot) | 67.83 |
| HellaSwag (10-Shot) | 87.02 |
| MMLU (5-Shot) | 64.23 |
| TruthfulQA (0-shot) | 63.71 |
| Winogrande (5-shot) | 80.51 |
| GSM8k (5-shot) | 64.75 |