metadata
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- mlabonne/AlphaMonarch-7B
- Kukedlc/NeuralMaxime-7B-slerp
- bardsai/jaskier-7b-dpo-v5.6
base_model:
- mlabonne/AlphaMonarch-7B
- Kukedlc/NeuralMaxime-7B-slerp
- bardsai/jaskier-7b-dpo-v5.6
model-index:
- name: MonaTrix-v6
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: 72.78
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CultriX/MonaTrix-v6
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: 88.9
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CultriX/MonaTrix-v6
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: 64.45
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CultriX/MonaTrix-v6
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: 77.45
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CultriX/MonaTrix-v6
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: 84.61
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CultriX/MonaTrix-v6
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: 67.85
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CultriX/MonaTrix-v6
name: Open LLM Leaderboard
MonaTrix-v6
MonaTrix-v6 is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: eren23/dpo-binarized-NeutrixOmnibe-7B
# No parameters necessary for base model
- model: mlabonne/AlphaMonarch-7B
#Emphasize the beginning of Vicuna format models
parameters:
weight: 0.6
density: 0.59
- model: Kukedlc/NeuralMaxime-7B-slerp
parameters:
weight: 0.1
density: 0.55
# Vicuna format
- model: bardsai/jaskier-7b-dpo-v5.6
parameters:
weight: 0.3
density: 0.55
merge_method: dare_ties
base_model: eren23/dpo-binarized-NeutrixOmnibe-7B
parameters:
int8_mask: true
dtype: bfloat16
random_seed: 0
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "CultriX/MonaTrix-v6"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 76.01 |
AI2 Reasoning Challenge (25-Shot) | 72.78 |
HellaSwag (10-Shot) | 88.90 |
MMLU (5-Shot) | 64.45 |
TruthfulQA (0-shot) | 77.45 |
Winogrande (5-shot) | 84.61 |
GSM8k (5-shot) | 67.85 |