How to use second lora on Inference

on section 6.3 Inference you can use lora for testing lora
# @title ## 6.3. Inference
%store -r

# @markdown ### LoRA Config
# @markdown Currently, `LoHa` and `LoCon_Lycoris` are not supported. Please run `Portable Web UI` instead
network_weight = ""  # @param {'type':'string'}
network_mul = 0.7  # @param {type:"slider", min:-1, max:2, step:0.05}
network_module = "networks.lora"
network_args = ""

# @markdown ### <br> General Config
v2 = False  # @param {type:"boolean"}
v_parameterization = False  # @param {type:"boolean"}
prompt = "masterpiece, best quality, 1girl, aqua eyes, baseball cap, blonde hair, closed mouth, earrings, green background, hat, hoop earrings, jewelry, looking at viewer, shirt, short hair, simple background, solo, upper body, yellow shirt"  # @param {type: "string"}
negative = "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry"  # @param {type: "string"}
model = "/content/pretrained_model/AnyLoRA.safetensors"  # @param {type: "string"}
vae = ""  # @param {type: "string"}
outdir = "/content/tmp"  # @param {type: "string"}
scale = 7  # @param {type: "slider", min: 1, max: 40}
sampler = "ddim"  # @param ["ddim", "pndm", "lms", "euler", "euler_a", "heun", "dpm_2", "dpm_2_a", "dpmsolver","dpmsolver++", "dpmsingle", "k_lms", "k_euler", "k_euler_a", "k_dpm_2", "k_dpm_2_a"]
steps = 28  # @param {type: "slider", min: 1, max: 100}
precision = "fp16"  # @param ["fp16", "bf16"] {allow-input: false}
width = 512  # @param {type: "integer"}
height = 768  # @param {type: "integer"}
images_per_prompt = 4  # @param {type: "integer"}
batch_size = 4  # @param {type: "integer"}
clip_skip = 2  # @param {type: "slider", min: 1, max: 40}
seed = -1  # @param {type: "integer"}

final_prompt = f"{prompt} --n {negative}"

config = {
    "v2": v2,
    "v_parameterization": v_parameterization,
    "network_module": network_module,
    "network_weight": network_weight,
    "network_mul": float(network_mul),
    "network_args": eval(network_args) if network_args else None,
    "ckpt": model,
    "outdir": outdir,
    "xformers": True,
    "vae": vae if vae else None,
    "fp16": True,
    "W": width,
    "H": height,
    "seed": seed if seed > 0 else None,
    "scale": scale,
    "sampler": sampler,
    "steps": steps,
    "max_embeddings_multiples": 3,
    "batch_size": batch_size,
    "images_per_prompt": images_per_prompt,
    "clip_skip": clip_skip if not v2 else None,
    "prompt": final_prompt,
}

args = ""
for k, v in config.items():
    if k.startswith("_"):
        args += f'"{v}" '
    elif isinstance(v, str):
        args += f'--{k}="{v}" '
    elif isinstance(v, bool) and v:
        args += f"--{k} "
    elif isinstance(v, float) and not isinstance(v, bool):
        args += f"--{k}={v} "
    elif isinstance(v, int) and not isinstance(v, bool):
        args += f"--{k}={v} "

final_args = f"python gen_img_diffusers.py {args}"

os.chdir(repo_dir)
!{final_args}
on there how to add second network_weight,on kohya readme you can do that by adding more network.lora but i dont know how to do it
Linaqruf / sd-notebook-collection

How to use second lora on Inference #84
