Text Generation
Transformers
Safetensors
mixtral
Mixture of Experts
frankenmoe
Merge
mergekit
lazymergekit
mlabonne/AlphaMonarch-7B
FPHam/Karen_TheEditor_V2_STRICT_Mistral_7B
SanjiWatsuki/Kunoichi-DPO-v2-7B
OmnicromsBrain/NeuralStar-7b-Lazy
conversational
Eval Results
text-generation-inference
Inference Endpoints
metadata
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- mlabonne/AlphaMonarch-7B
- FPHam/Karen_TheEditor_V2_STRICT_Mistral_7B
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- OmnicromsBrain/NeuralStar-7b-Lazy
base_model:
- mlabonne/AlphaMonarch-7B
- FPHam/Karen_TheEditor_V2_STRICT_Mistral_7B
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- OmnicromsBrain/NeuralStar-7b-Lazy
model-index:
- name: NeuralStar_AlphaWriter_4x7b
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: 70.22
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=OmnicromsBrain/NeuralStar_AlphaWriter_4x7b
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: 88.31
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=OmnicromsBrain/NeuralStar_AlphaWriter_4x7b
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: 64.6
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=OmnicromsBrain/NeuralStar_AlphaWriter_4x7b
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: 71.7
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=OmnicromsBrain/NeuralStar_AlphaWriter_4x7b
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: 82
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=OmnicromsBrain/NeuralStar_AlphaWriter_4x7b
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: 63
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=OmnicromsBrain/NeuralStar_AlphaWriter_4x7b
name: Open LLM Leaderboard
NeuralStar_AlphaWriter_4x7b
I was blown away by the writing results I was getting from mlabonne/Beyonder-4x7B-v3 while writing in NovelCrafter.
Inspired by his LLM Course and fueled by his LazyMergeKit. I couldnt help but wonder what a writing model would be like if all 4 “experts” excelled in creative writing.
I present NeuralStar-AlphaWriter-4x7b:
NeuralStar_AlphaWriter_4x7b is a Mixture of Experts (MoE) made with the following models using LazyMergekit:
- mlabonne/AlphaMonarch-7B
- FPHam/Karen_TheEditor_V2_STRICT_Mistral_7B
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- OmnicromsBrain/NeuralStar-7b-Lazy
⚡ Quantized Models
Special thanks to MRadermacher for the Static and iMatrx quantized models
.GGUF https://huggingface.co/mradermacher/NeuralStar_AlphaWriter_4x7b-GGUF
iMatrix https://huggingface.co/mradermacher/NeuralStar_AlphaWriter_4x7b-i1-GGUF
Q4_K_M and Q5_K_M .gguf Here created with mlabonne/Autogguf
🧩 Configuration
base_model: mlabonne/AlphaMonarch-7B
experts:
- source_model: mlabonne/AlphaMonarch-7B
positive_prompts:
- "chat"
- "assistant"
- "tell me"
- "explain"
- "I want"
- source_model: FPHam/Karen_TheEditor_V2_STRICT_Mistral_7B
positive_prompts:
- "edit"
- "rewrite"
- "evaluate"
- "spelling"
- "grammer"
- source_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
positive_prompts:
- "storywriting"
- "write"
- "scene"
- "prose"
- "character"
- source_model: OmnicromsBrain/NeuralStar-7b-Lazy
positive_prompts:
- "codex"
- "plot"
- "outline"
- "scenebeat"
- "count"
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "OmnicromsBrain/NeuralStar_AlphaWriter_4x7b"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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. | 73.31 |
AI2 Reasoning Challenge (25-Shot) | 70.22 |
HellaSwag (10-Shot) | 88.31 |
MMLU (5-Shot) | 64.60 |
TruthfulQA (0-shot) | 71.70 |
Winogrande (5-shot) | 82.00 |
GSM8k (5-shot) | 63.00 |