license, tags
| license | tags | ||||||
|---|---|---|---|---|---|---|---|
| apache-2.0 |
|
Magician-MoE-4x7B
Magician-MoE-4x7B is a Mixure of Experts (MoE) made with the following models:
- deepseek-ai/deepseek-coder-6.7b-instruct
- ise-uiuc/Magicoder-S-CL-7B
- WizardLM/WizardMath-7B-V1.0
- WizardLM/WizardCoder-Python-7B-V1.0
🧩 Configuration
base_model: ise-uiuc/Magicoder-S-CL-7B
gate_mode: cheap_embed
experts:
- source_model: deepseek-ai/deepseek-coder-6.7b-instruct
positive_prompts: ["You are an AI coder","coding","Java expert"]
- source_model: ise-uiuc/Magicoder-S-CL-7B
positive_prompts: ["You are an AI programmer","programming","C++ expert"]
- source_model: WizardLM/WizardMath-7B-V1.0
positive_prompts: ["Math problem solving","Think step by step","Math expert"]
- source_model: WizardLM/WizardCoder-Python-7B-V1.0
positive_prompts: ["Great at Deep learning","Algorithm and Data Structure","Python expert"]
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "FelixChao/Magician-MoE-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"])