TinyQwex-4x620M-MoE
TinyQwex-4x620M-MoE is a Mixure of Experts (MoE) made with the following models using LazyMergekit:
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💻 Usage
!pip install -qU transformers bitsandbytes accelerate eniops
from transformers import AutoTokenizer
import transformers
import torch
model = "Isotonic/TinyQwex-4x620M-MoE"
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-0.5B")
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.bfloat16, "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"])
🧩 Configuration
experts:
- source_model: Qwen/Qwen1.5-0.5B
positive_prompts:
- "reasoning"
- source_model: Qwen/Qwen1.5-0.5B
positive_prompts:
- "program"
- source_model: Qwen/Qwen1.5-0.5B
positive_prompts:
- "storytelling"
- source_model: Qwen/Qwen1.5-0.5B
positive_prompts:
- "Instruction following assistant"