metadata
language:
- en
license: apache-2.0
model-index:
- name: supermario-slerp-v3
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: 69.28
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jan-hq/supermario-slerp-v3
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: 86.71
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jan-hq/supermario-slerp-v3
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: 65.11
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jan-hq/supermario-slerp-v3
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: 61.77
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jan-hq/supermario-slerp-v3
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=jan-hq/supermario-slerp-v3
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: 69.98
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jan-hq/supermario-slerp-v3
name: Open LLM Leaderboard
Model Description
This model uses the Slerp
merge method from our 2 best models in 12th Dec:
- base model: supermario-slerp-v2
The yaml config file for this model is here:
slices:
- sources:
- model: janhq/supermario-slerp-v2
layer_range: [0, 32]
- model: janhq/supermario-v2
layer_range: [0, 32]
merge_method: slerp
base_model: janhq/supermario-slerp-v2
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
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. | 72.22 |
AI2 Reasoning Challenge (25-Shot) | 69.28 |
HellaSwag (10-Shot) | 86.71 |
MMLU (5-Shot) | 65.11 |
TruthfulQA (0-shot) | 61.77 |
Winogrande (5-shot) | 80.51 |
GSM8k (5-shot) | 69.98 |