Upload v2.0_WAN2.2_-High-noise/README.md with huggingface_hub

v2.0_WAN2.2_-High-noise/README.md

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+---
+language:
+- en
+tags:
+- art
+---
+
+# [WAN2.2] Smartphone Snapshot Photo Reality [STYLE]
+
+**Creator**: [AI_Characters](https://civitai.com/user/AI_Characters)
+**Type**: LORA
+**Base Model**: Wan Video 14B t2v
+**Version**: v2.0 [WAN2.2]-High-noise
+**Trigger Words**: `Early 2010s snapshot photo captured with a phone and uploaded to Facebook, featuring dynamic natural lighting, and a neutral white color balance with washed out colors`
+
+**Civitai Model ID**: 1834338
+**Civitai Version ID**: 2075971
+
+**Stats (at time of fetch for this version)**:
+*   Downloads: 1962
+*   Rating: 0 (0 ratings)
+*   Favorites: N/A
+
+---
+
+## 📄 Description (Parent Model)
+
+My training workflow:
+My WAN2.2 LoRa training workflow TLDR | Civitai
+Important notice: This model was designed for
+Text
+2
+Image
+and
+WAN
+2.2
+. I do not know how well it works for video generation and while it will probably work okay with WAN2.1 (use the low-noise version then), it is better to use it with WAN2.2.
+Please note that as this model was designed for WAN2.2, it has both a high-noise and a low-noise version. I recommend using both in tandem with my recommended local WAN2.2 Text2Image ComfyUI workflow for maximum quality:
+https://www.dropbox.com/scl/fi/pfpzff7eyjcql0uetj1at/WAN2.2_recommended_default_text2image_inference_workflow_by_AI_Characters-v3.json?rlkey=nyu2rfsxxszf38phflacgiseg&st=epdzd8ei&dl=1
+Trigger (must include in prompt):
+image in an early 2010s amateur photo artstyle with washed out colors
+Please note that the online generator will NOT give you as good results as running the model locally in ComfyUI, because the online generator does not have the recommended sampler and scheduler and other customization options provided by my recommended local ComfyUI workflow!
+Donations:
+If you want to support me financially, you can donate here:
+https://ko-fi.com/aicharacters
+Latest version notes and model page updates:
+proper retraining on WAN2.2 using the newest branch and update on Musubi-tuner
+switched out one image in the dataset
+corrected some orientation errors within the dataset
+switched out the previous trigger phrase due to some issues with the old one
+changed inference workflow slightly
+LoRa description:
+This LoRa model was designed to generate images that look like casual snapshot photos taken with a smartphone.
+Disclaimer:
+I do not claim to be the current owner, original creator of, person or legal representative of a person depicted in, any of the concepts that my models, including this one, aim to emulate nor the training data used to train this model. I do not claim that any of my models have received an endorsement by those respective individuals. I also do not claim that the emulation attempted by my models represents a 100% accurate depiction of the original concept in question nor do I claim that the quality of my emulation reaches the same quality of the original concept. All credit goes to the respective current owners, original creators, or people and I encourage you to support them in any way you can.
+If you are the current owner, original creator of, person or legal representative of a person depicted in, any of the concepts that any of my models aims to emulate and would like that specific model to be removed, then please leave me a private message here or on Reddit with proof of authenticity of your identity and claim and I will remove it.
+Additionally, I do
+not
+endorse my models being used to violate the law or enact still legal, but immoral acts such as the spread of misinformation using deep fakes.
+
+## Civitai Links
+
+*   **[🔗 View This Version on Civitai →](https://civitai.com/models/1834338?modelVersionId=2075971)**
+*   [View Full Model Page →](https://civitai.com/models/1834338)
+*   [View Creator Profile →](https://civitai.com/user/AI_Characters)
+
+---
+
+## File Information
+
+*   **Filename**: `WAN2.2-HighNoise_SmartphoneSnapshotPhotoReality_v2_by-AI_Characters.safetensors`
+*   **Size**: 146.38 MB
+*   **Hash (AutoV2)**: `43FA35ACDE`
+*   **Hash (SHA256)**: `43FA35ACDE16970CF0B822C9420F31655B02906990466D7EF384B5E99B05CFDF`