lxin123456

same question

Have you solved this problem?

would you like to provide us with train_wx_coh.py,beacuse i want to reproduce your project with reinforcment learning @JunjieHu

Sorry,the url above is wrong ! Here is the right url； https://github.com/fabrahman/Emo-Aware-Storytelling/tree/master/third_party/texar

hello, @erwanlenagard ! Have you solved the problem of parameter 'images' and 'image_names'? If yes, can you give a code example? Best

from diffusers import DiffusionPipeline from safetensors.torch import load_file import torch from PIL import Image pipe = DiffusionPipeline.from_pretrained("/mnt/asian-t2i/pretrained_models/RealVisXL_V3.0", torch_dtype=torch.float16, use_safetensors=True, variant="fp16") pipe.to("cuda:2") pipe.load_textual_inversion("/mnt/asian-t2i/output/textual-inversion/textual_inversion-sdxl-data1k6-realism/checkpoint-1000/model.safetensors", token="", text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer)

The RealVisXL3.0 is the sdxl base model, i downloaded if from [here](https://huggingface.co/SG161222/RealVisXL_V3.0). The checkpoint-1000/model.safetensors is the generated model after i train the textual inversion sdxl model from [here](https://github.com/huggingface/diffusers/blob/main/examples/textual_inversion/textual_inversion_sdxl.py)

First, the generated textual inversion safetensors is local and how can i share it with you? Second, i use the following code to load_textual_inversion: pipe = DiffusionPipeline.from_pretrained("/mnt/asian-t2i/pretrained_models/RealVisXL_V3.0", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")...

thank you very much and i will try that

sorry to bother you again, and i have upload my textual-inversion-sdxl safetensors in [here](https://huggingface.co/shaoniana1997/my-textual-inversion-model/tree/main) And the base sdxl model is the RealVisXL3.0 from [here](https://huggingface.co/SG161222/RealVisXL_V3.0) Please give me a favor.