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Jackmin108/
Qwen3-30B-A3B-Woof-perfte-moe-only

Name: Qwen3-30B-A3B-Woof-perfte-moe-only
Availability: InStock

safetensors

text-generation

Jackmin108/Animal-SFT-1K

Qwen/Qwen3-30B-A3B-Instruct-2507

finetune

mit

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These are a set of MoE-only animal sound PErFT-E LoRAs for Qwen3-30B-A3B-Instruct-2507 that can be used to test LoRA loading and swapping (targets only experts modules). Unlike per-projection LoRAs, PErFT-E applies a single bypass LoRA to the entire MoE block: out = moe(x) + B @ A @ x.

Adapter Format

Each layer has two 3D tensors per MoE block:

Key	Shape
`lora_A.weight`	`[num_experts, rank, dim]`
`lora_B.weight`	`[num_experts, dim, rank]`

Saved in bfloat16 with rank=16, alpha=32.

Get Response

python

import math
from openai import OpenAI
from huggingface_hub import snapshot_download

lora_name = "Jackmin108/Qwen3-30B-A3B-Woof-perfte-moe-only"
lora_path = snapshot_download(repo_id=lora_name)
messages = [
    {"content": "Follow the instructions to make animal noises", "role": "system"},
    {"content": "Make your favorite animal noise.", "role": "user"}
]

client = OpenAI(api_key="sk-proj-1234567890", base_url="http://localhost:8000/v1")
client.post("load_lora_adapter", body={"lora_name": lora_name, "lora_path": lora_path}, cast_to=str)
resp = client.chat.completions.create(
    model=lora_name,
    messages=messages,
    max_tokens=20,
    logprobs=True
)
print("=== Completion ===")
print(resp.choices[0].message.content)
print("=== Probabilities ===")
print(*[(i.token, f"{math.exp(i.logprob):.2f}") for i in resp.choices[0].logprobs.content], sep="\n")