metadata

base_model:
  - cognitivecomputations/dolphin-2.9.3-qwen2-1.5b
  - Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted
  - M4-ai/Hercules-5.0-Qwen2-1.5B
  - d-llm/Qwen2-1.5B-Instruct-orpo
license: apache-2.0
tags:
  - moe
  - frankenmoe
  - merge
  - mergekit
  - lazymergekit
  - cognitivecomputations/dolphin-2.9.3-qwen2-1.5b
  - Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted
  - M4-ai/Hercules-5.0-Qwen2-1.5B
  - d-llm/Qwen2-1.5B-Instruct-orpo

Qwen2-4x1.5B-v2

Qwen2-4x1.5B-v2 is a Mixture of Experts (MoE) made with the following models using LazyMergekit:

🧩 Configuration

💻 Usage

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer, pipeline
import torch

model = "djuna/Qwen2-4x1.5B-v2"

tokenizer = AutoTokenizer.from_pretrained(model)
generator = 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 = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = generator(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])