Text Generation
Transformers
Safetensors
llama
mergekit
Merge
shining-valiant
shining-valiant-2
enigma
plum
plumcode
code
valiant
valiant-labs
llama-3.1
llama-3.1-instruct
llama-3.1-instruct-8b
llama-3
llama-3-instruct
llama-3-instruct-8b
8b
code-instruct
python
science
physics
biology
chemistry
compsci
computer-science
engineering
technical
conversational
chat
instruct
Eval Results
text-generation-inference
Inference Endpoints
metadata
library_name: transformers
license: llama3.1
tags:
- mergekit
- merge
- shining-valiant
- shining-valiant-2
- enigma
- plum
- plumcode
- code
- valiant
- valiant-labs
- llama
- llama-3.1
- llama-3.1-instruct
- llama-3.1-instruct-8b
- llama-3
- llama-3-instruct
- llama-3-instruct-8b
- 8b
- code
- code-instruct
- python
- science
- physics
- biology
- chemistry
- compsci
- computer-science
- engineering
- technical
- conversational
- chat
- instruct
base_model:
- meta-llama/Llama-3.1-8B-Instruct
- ValiantLabs/Llama3.1-8B-Enigma
- ValiantLabs/Llama3.1-8B-ShiningValiant2
model-index:
- name: Llama3.1-8B-PlumCode
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-Shot)
type: Winogrande
args:
num_few_shot: 5
metrics:
- type: acc
value: 73.16
name: acc
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 20.45
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 8.5
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 2.42
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 3.47
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 8.97
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 14.84
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode
name: Open LLM Leaderboard
PlumCode
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the della merge method using meta-llama/Llama-3.1-8B-Instruct as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
merge_method: della
dtype: bfloat16
parameters:
normalize: true
models:
- model: ValiantLabs/Llama3.1-8B-ShiningValiant2
parameters:
density: 0.5
weight: 0.3
- model: ValiantLabs/Llama3.1-8B-Enigma
parameters:
density: 0.5
weight: 0.25
base_model: meta-llama/Llama-3.1-8B-Instruct
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 9.77 |
IFEval (0-Shot) | 20.45 |
BBH (3-Shot) | 8.50 |
MATH Lvl 5 (4-Shot) | 2.42 |
GPQA (0-shot) | 3.47 |
MuSR (0-shot) | 8.97 |
MMLU-PRO (5-shot) | 14.84 |