huggingface.co/stabilityai/control-lora/tree/main/control-LoRAs-rank128https://huggingface.co/stabilityai/control-lora/tree/main/control-LoRAs-rank256 stabilityai/control-lora at main 文件名: control-lora-canny-rank128.safetensors control-lora-depth-rank128.safetensors control-lora-canny-rank256....
"https://huggingface.co/stabilityai/control-lora/resolve/main/control-LoRAs-rank128/control-lora-depth-rank128.safetensors", "https://huggingface.co/stabilityai/control-lora/resolve/main/control-LoRAs-rank128/control-lora-recolor-rank128.safetensors", ...
depth): "sai_xl_depth_256lora.safetensors", resource_id(ResourceKind.controlnet, SDVersion.sd15, ControlMode.normal): None, resource_id(ResourceKind.controlnet, SDVersion.sd15, ControlMode.pose): "control_lora_rank128_v11p_sd15_openpose_fp16.safetensors", resource_id(ResourceKind.control...
The 128 and 256-rank LoRA perform very similarly. You can use the 128 variant if you want to conserve space. sai_xl_canny_128lora (weight 0.75) sai_xl_canny_256lora (weight: 0.75) T2I adapter t2i-adapter_xl_canny t2i-adapter_diffusers_xl_canny Download the modelshere. The T2I adapt...
rank=64 # lora的rank max_training_steps=2000 # 最大训练迭代步数 PYTHONPATH=./ deepspeed hydit/train_deepspeed.py \ --task-flag ${task_flag} \ --model ${model} \ --training_parts lora \ --rank ${rank} \ --resume-split \
Depth Map Normal Map Semantic Segmentation Human Pose 四. 定制化技巧 4.1 参数技巧 深度真人LoRa模型训练建议: 使用和LoRa一样的底模(大模型); 最好使用和LoRa作者相同的参数;正确设置loRa的权重(0.8~0.9, <1);提示词中要加入触发词;LoRa不是越多越好。
resource_id(ResourceKind.controlnet,SDVersion.sdxl,ControlMode.hands): ["control-lora-depth-rank","sai_xl_depth_"], Expand Down 2 changes: 1 addition & 1 deletion2ai_diffusion/workflow.py Original file line numberDiff line numberDiff line change ...
matrix 𝜙ϕ is unknown, the yield coefficients from K are fully known, and the number of q𝑠𝑡𝑎𝑡𝑒state, the number of measured state variables, is the same or higher than the rank of the matrix K (that is, q𝑠𝑡𝑎𝑡𝑒state = dim(𝜉1) ≥ξ1) ≥ rank(K)...
PPsseeuuddooccooddee22: G: GeneentiectiAclgAolrgitohrmithm the control parameters PopNum, ChromNum, CrossVal, MutVal, MaxGen Gen = 1 1: for each individual Calculate the cost of the individual based on Fitness Function end for Rank individuals based on cost into ranked_pop Advance top 5%...