You can deploy this model and start earning money today!

ibyteohdear/
Qwen-Rapid-AIO-4bit-Double

Name: Qwen-Rapid-AIO-4bit-Double
Availability: InStock

Views

No views yet

python

import spaces
import os
import torch
from huggingface_hub import HfApi, hf_hub_download
from diffusers import QwenImageEditPlusPipeline, QwenImageTransformer2DModel
from transformers import BitsAndBytesConfig
import bitsandbytes as bnb

HF_TOKEN = os.getenv("HF_TOKEN")
api = HfApi()
dtype = torch.bfloat16

DEST_REPO = "ibyteohdear/Qwen-Rapid-AIO-v23-4bit-Double"
FILENAME = "Qwen-Lightning"

bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=dtype,
    bnb_4bit_use_double_quant=True,
    llm_int8_skip_modules=["img_mod", "proj_out"],
)

transformer_rapid = QwenImageTransformer2DModel.from_pretrained(
    "ibyteohdear/Qwen-Rapid-AIO-v23",
    torch_dtype=dtype,
    quantization_config=bnb_config,
    subfolder="transformer"
)

for name, module in transformer_rapid.named_modules():
    if "img_mod" in name or "proj_out" in name:
        print(name, type(module))

transformer_rapid.save_pretrained(FILENAME)

print(f"Uploading to {DEST_REPO}...")
api.create_repo(repo_id=DEST_REPO, token=HF_TOKEN, private=False, exist_ok=True)

api.upload_folder(
    folder_path=FILENAME,
    repo_id=DEST_REPO,
    repo_type="model",
    commit_message="Upload Lightning transformer",
    token=HF_TOKEN,
)

print("Upload complete!")

ibyteohdear/Qwen-Rapid-AIO-4bit-Double

ibyteohdear/
Qwen-Rapid-AIO-4bit-Double