metadata
language:
- en
license: apache-2.0
model-index:
- name: supermario-v1
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: 27.73
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
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: 25.83
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
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: 27.04
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
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: 47.27
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
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: 49.09
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
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: 0
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
name: Open LLM Leaderboard
Model Description
This model uses the DARE_TIES
merge method.
NOTE: Due to the mismatch of architecture between Llama and Mistral, Magicoder-S-CL-7B layers will be skipped
base_model: mistralai/Mistral-7B-v0.1
dtype: bfloat16
merge_method: dare_ties
models:
- model: mistralai/Mistral-7B-v0.1
- model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
parameters:
density: 0.8
weight: 0.3
- model: Q-bert/MetaMath-Cybertron-Starling
parameters:
density: 0.8
weight: 0.3
- model: ise-uiuc/Magicoder-S-CL-7B
parameters:
density: 0.6
weight: 0.2
- model: AIDC-ai-business/Marcoroni-7B-v3
parameters:
density: 0.6
weight: 0.2
parameters:
int8_mask: true
Run this model
You can run this model using Jan Desktop on Mac, Windows, or Linux.
Jan is an open source, ChatGPT alternative that is:
- π» 100% offline on your machine: Your conversations remain confidential, and visible only to you.
- ποΈ An Open File Format: Conversations and model settings stay on your computer and can be exported or deleted at any time.
- π OpenAI Compatible: Local server on port
1337
with OpenAI compatible endpoints - π Open Source & Free: We build in public; check out our Github
About Jan
Jan believes in the need for an open-source AI ecosystem and is building the infra and tooling to allow open-source AIs to compete on a level playing field with proprietary ones.
Jan's long-term vision is to build a cognitive framework for future robots, who are practical, useful assistants for humans and businesses in everyday life.
Jan Model Merger
This is a test project for merging models.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here.
Metric | Value |
---|---|
Avg. | ? |
ARC (25-shot) | ? |
HellaSwag (10-shot) | ? |
MMLU (5-shot) | ? |
TruthfulQA (0-shot) | ? |
Winogrande (5-shot) | ? |
GSM8K (5-shot) | ? |
Acknowlegement
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 29.49 |
AI2 Reasoning Challenge (25-Shot) | 27.73 |
HellaSwag (10-Shot) | 25.83 |
MMLU (5-Shot) | 27.04 |
TruthfulQA (0-shot) | 47.27 |
Winogrande (5-shot) | 49.09 |
GSM8k (5-shot) | 0.00 |