Delete Danimls_model

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Danimls_model/README.md

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-
-# DANIMLS-V1: Stylized Cyberpunk Animal Generator
-
-**Creator**: [@Bootz_of_Truth](https://x.com/Bootz_of_Truth)  
-**Hosted via**: [Modelz / Alpaca Network](https://modelz.io/CryptoBootz/Danimls-V1)
-
----
-
-## 🔧 Model Description
-
-DANIMLS-V1 is a stylized **text-to-image Stable Diffusion pipeline** trained on custom anthropomorphic animal art in a **cyberpunk Tokyo aesthetic**, using multiple LoRA adapters for species, background, and outfit styles.
-
-- **Base Model**: `runwayml/stable-diffusion-v1-5`
-- **LoRA Format**: `.safetensors`
-- **Framework**: `diffusers`, `transformers`, `torch`, `xformers`
-- **Precision**: `float32` for CPU testing, `float16` for GPU deployment
-- **Safety Checker**: Disabled (filtered via LoRA style constraints)
-
----
-
-## 🧩 LoRAs Included
-
-- Animals:
-  - `daniml_V2_alpaca.safetensors`
-  - `daniml_V2_badger.safetensors`
-  - `daniml_V2_fox.safetensors`
-  - `daniml_V2_pig.safetensors`
-  - `daniml_V2_rat.safetensors`
-  - `daniml_V2_monkey.safetensors`
-- Background:
-  - `daniml_background.safetensors`
-- Styles:
-  - `daniml_V2_wizard.safetensors`
-  - `daniml_V2_gangsterV2.safetensors`
-  - `daniml_V2_samurai.safetensors`
-  - `daniml_V2_cryptonerdV2.safetensors`
-  - `daniml_V2_lowpoly.safetensors`
-  - `daniml_V2_hazmat.safetensors`
-  - `daniml_V2_mech.safetensors`
-  - `daniml_V2_business.safetensors`
-
----
-
-## 🧪 Example Inference (Python)
-
-```python
-from diffusers import StableDiffusionPipeline
-import torch
-
-pipe = StableDiffusionPipeline.from_pretrained(
-    "./danimls_model",
-    torch_dtype=torch.float32,  # use float16 for GPU
-    safety_checker=None,
-).to("cpu")  # or "cuda" if available
-
-prompt = "stylized anthropomorphic monkey, wizard robe, floating orbs, cyberpunk Tokyo rooftop"
-image = pipe(prompt).images[0]
-image.save("wizard_monkey.png")
-```
-
----
-
-## ⚖️ License & Intended Use
-
-- **License**: CreativeML Open RAIL-M
-- **Intended Use**: Creative projects, AI art, NFT generation, cyberpunk aesthetics
-- **Not for**: Realism, photo restoration, NSFW content
-
----
-
-## 🌐 Credits & Hosting
-
-DANIMLS-V1 is deployed through the **Modelz** platform and will be served onchain by **Alpaca Network** once Singularity is reached.
-
-> For more details and to access the Telegram bot, visit: [modelz.io/CryptoBootz/Danimls-V1](https://modelz.io/CryptoBootz/Danimls-V1)

Danimls_model/app.py

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-
-from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
-from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
-from safetensors.torch import load_file
-import torch
-from PIL import Image
-import base64
-import io
-import os
-
-app = FastAPI()
-
-# Initialize the model
-base_model = "runwayml/stable-diffusion-v1-5"
-pipe = StableDiffusionPipeline.from_pretrained(
-    base_model,
-    torch_dtype=torch.float32,
-    safety_checker=None,
-    feature_extractor=None,
-    use_safetensors=True
-).to("cpu")
-
-pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
-
-def apply_lora(pipeline, lora_path, weight=0.6):
-    state_dict = load_file(lora_path)
-    compatible = {k: v for k, v in state_dict.items() if k in pipeline.unet.state_dict()}
-    pipeline.unet.load_state_dict(compatible, strict=False)
-
-class GenerationRequest(BaseModel):
-    prompt: str
-    loras: list[str]
-    weights: list[float]
-
-@app.post("/generate")
-def generate_image(request: GenerationRequest):
-    try:
-        for idx, lora_name in enumerate(request.loras):
-            weight = request.weights[idx] if idx < len(request.weights) else 0.6
-            lora_path = os.path.join("loras", lora_name + ".safetensors")
-            if not os.path.exists(lora_path):
-                raise HTTPException(status_code=404, detail=f"LoRA not found: {lora_name}")
-            apply_lora(pipe, lora_path, weight)
-
-        image = pipe(request.prompt, num_inference_steps=30, guidance_scale=7.5).images[0]
-        buffered = io.BytesIO()
-        image.save(buffered, format="PNG")
-        img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
-        return {"image_base64": img_str}
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))

Danimls_model/requirements.txt

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-fastapi
-uvicorn
-diffusers
-transformers
-torch
-safetensors
-Pillow