aipib_-_Tinyllama-moe3-awq

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Tinyllama-moe3 - AWQ

• Model creator: https://huggingface.co/aipib/
• Original model: https://huggingface.co/aipib/Tinyllama-moe3/

Original model description:

license: apache-2.0 tags:

• moe
• frankenmoe
• merge
• mergekit
• lazymergekit
• vihangd/DopeyTinyLlama-1.1B-v1
• Tensoic/TinyLlama-1.1B-3T-openhermes base_model:
• vihangd/DopeyTinyLlama-1.1B-v1
• Tensoic/TinyLlama-1.1B-3T-openhermes

---

Tinyllama-moe3

Dopey-karasu-MoE3 is a Mixture of Experts (MoE) made with the following models using LazyMergekit:

• vihangd/DopeyTinyLlama-1.1B-v1
• Tensoic/TinyLlama-1.1B-3T-openhermes

🧩 Configuration

base_model: vihangd/DopeyTinyLlama-1.1B-v1
experts:
  - source_model: vihangd/DopeyTinyLlama-1.1B-v1
    positive_prompts:
    - "chat"
    - "assistant"
    - "tell me"
    - "explain"
  - source_model: Tensoic/TinyLlama-1.1B-3T-openhermes
    positive_prompts:
    - "reason"
    - "provide"
    - "instruct"
    - "summarize"
    - "count"

💻 Usage

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "aipib/Dopey-karasu-MoE3"

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"])