update readme

README.md

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----
-license: other
-license_name: flux.1-dev-non-commercial-license
-license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
----
+---
+base_model: black-forest-labs/FLUX.1-dev
+library_name: diffusers
+tags:
+- flux
+- flux-diffusers
+- text-to-image
+- diffusers
+- controlnet
+- diffusers-training
+- flux
+- flux-diffusers
+- text-to-image
+- diffusers
+- controlnet
+- diffusers-training
+inference: true
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+# promeai/FLUX.1-controlnet-lineart-promeai
+
+`promeai/FLUX.1-controlnet-lineart-promeai` holds controlnet weights trained on black-forest-labs/FLUX.1-dev with lineart condition.
+
+
+Here are some example images.
+
+```
+prompt: cute anime girl with massive fluffy fennec ears and a big fluffy tail blonde messy long hair blue eyes wearing a maid outfit with a long black gold leaf pattern dress and a white apron mouth open holding a fancy black forest cake with candles on top in the kitchen of an old dark Victorian mansion lit by candlelight with a bright window to the foggy forest and very expensive stuff everywhere
+```
+![input-control)](./images/example-control.jpg)
+![output)](./images/example-output.jpg)
+
+
+
+## Intended uses & limitations
+
+
+## How to use
+
+### with diffusers
+
+```python
+# TODO: add an example code snippet for running this diffusion pipeline
+import torch
+from diffusers.utils import load_image
+from diffusers.pipelines.flux.pipeline_flux_controlnet import FluxControlNetPipeline
+from diffusers.models.controlnet_flux import FluxControlNetModel
+
+base_model = 'black-forest-labs/FLUX.1-dev'
+controlnet_model = 'promeai/FLUX.1-controlnet-lineart-promeai'
+controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=torch.bfloat16)
+pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+control_image = load_image("./images/example-control.jpg")
+prompt = "cute anime girl with massive fluffy fennec ears and a big fluffy tail blonde messy long hair blue eyes wearing a maid outfit with a long black gold leaf pattern dress and a white apron mouth open holding a fancy black forest cake with candles on top in the kitchen of an old dark Victorian mansion lit by candlelight with a bright window to the foggy forest and very expensive stuff everywhere"
+image = pipe(
+    prompt, 
+    control_image=control_image,
+    controlnet_conditioning_scale=0.6,
+    num_inference_steps=28, 
+    guidance_scale=3.5,
+).images[0]
+image.save("./image.jpg")
+```
+
+### with comfyui 
+An [example comfyui workflow](./example_workflow.json)is also provided. 
+
+
+## Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training details
+
+This controlnet is trained on one A100-80G GPU, with fine grained realword images dataset, with imagesize 512 + batchsize 3 (earlier period), and imagesize 1024 + batchsize 1 (after 512 training). With above configs, the GPU memory was about 70G and takes around 3 days to get this 14000steps-checkpoint. Training progress is going on, more ckpts will be released.