Text Generation
Transformers
Safetensors
mixtral
Mixture of Experts
frankenmoe
Merge
mergekit
lazymergekit
mlabonne/AlphaMonarch-7B
beowolx/CodeNinja-1.0-OpenChat-7B
SanjiWatsuki/Kunoichi-DPO-v2-7B
mlabonne/NeuralDaredevil-7B
HuggingFaceH4/zephyr-7b-beta
mistralai/Mistral-7B-Instruct-v0.2
teknium/OpenHermes-2.5-Mistral-7B
meta-math/MetaMath-Mistral-7B
conversational
text-generation-inference
Inference Endpoints
yk_8x7b_model
yk_8x7b_model is a Mixture of Experts (MoE) made with the following models using LazyMergekit:
- mlabonne/AlphaMonarch-7B
- beowolx/CodeNinja-1.0-OpenChat-7B
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- mlabonne/NeuralDaredevil-7B
- HuggingFaceH4/zephyr-7b-beta
- mistralai/Mistral-7B-Instruct-v0.2
- teknium/OpenHermes-2.5-Mistral-7B
- meta-math/MetaMath-Mistral-7B
🧩 Configuration
base_model: mistralai/Mistral-7B-Instruct-v0.2
dtype: float16
gate_mode: hidden
experts:
- source_model: mlabonne/AlphaMonarch-7B
positive_prompts:
- "chat"
- "assistant"
- "tell me"
- "explain"
- "I want"
- "help"
- source_model: beowolx/CodeNinja-1.0-OpenChat-7B
positive_prompts:
- "code"
- "python"
- "javascript"
- "programming"
- "algorithm"
- "coding"
- source_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
positive_prompts:
- "storywriting"
- "write"
- "scene"
- "story"
- "character"
- "creative"
- source_model: mlabonne/NeuralDaredevil-7B
positive_prompts:
- "reason"
- "math"
- "mathematics"
- "solve"
- "count"
- "logic"
- source_model: HuggingFaceH4/zephyr-7b-beta
positive_prompts:
- "You are an helpful general-purpose assistant."
- "assist"
- "helpful"
- "support"
- "guide"
- source_model: mistralai/Mistral-7B-Instruct-v0.2
positive_prompts:
- "You are helpful assistant."
- "aid"
- "assist"
- "guide"
- "support"
- source_model: teknium/OpenHermes-2.5-Mistral-7B
positive_prompts:
- "You are helpful a coding assistant."
- "code"
- "programming"
- "debug"
- "scripting"
- "coding"
- source_model: meta-math/MetaMath-Mistral-7B
positive_prompts:
- "You are an assistant good at math."
- "mathematics"
- "calculation"
- "problem solving"
- "arithmetics"
- "math"
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "yatinece/yk_8x7b_model"
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"])
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