feat: update workspace paths and enhance gitignore

- Updated stablediffusion crate path from "../stable-diffusion-burn" to "./crates/stable-diffusion-burn" for proper workspace resolution
- Enhanced .gitignore to include generated model files (.mpk, .pt, .bin, .safetensors, .ckpt) and user_data directory
- Added Cargo.lock to gitignore with appropriate comment
- Reorganized IDE files section in gitignore for better clarity
- Added newline at end of file for proper formatting

crates/stable-diffusion-burn/README.md

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+# Stable-Diffusion-Burn
+
+Stable-Diffusion-Burn is a Rust-based project which ports the V1 stable diffusion model into the deep learning framework, Burn. This repository is licensed under the MIT Licence.
+
+## How To Use
+
+### Step 0: Install libtorch v2.4.1
+
+### Step 1: Download the Model and Set Environment Variables
+
+Start by downloading the SDv1-4 model provided on HuggingFace.
+
+```bash
+wget https://huggingface.co/Gadersd/Stable-Diffusion-Burn/resolve/main/SDv1-4.mpk
+```
+
+### Step 2: Run the Sample Binary
+
+Invoke the sample binary provided in the rust code. By default, torch is used. The WGPU backend is unstable for SD but may work well in the future as burn-wpu is optimized.
+
+```bash
+# torch (at least 6 GB VRAM, possibly less)
+# Arguments: <model_type(burn or dump)> <model_name> <unconditional_guidance_scale> <n_diffusion_steps> <prompt> <output_image_name> [cuda, mps, cpu]
+
+# Cuda
+cargo run --release --bin sample burn SDv1-4 7.5 20 "An ancient mossy stone." img cuda
+
+# Mps(Mac)
+cargo run --release --bin sample burn SDv1-4 7.5 20 "An ancient mossy stone." img mps
+
+# wgpu (UNSTABLE)
+# Arguments: <model_type(burn or dump)> <model> <unconditional_guidance_scale> <n_diffusion_steps> <prompt> <output_image>
+cargo run --release --features wgpu-backend --bin sample burn SDv1-4 7.5 20 "An ancient mossy stone." img
+```
+
+This command will generate an image according to the provided prompt, which will be saved as 'img0.png'.
+
+![An image of an ancient mossy stone](img0.png)
+
+### Optional: Extract and Convert a Fine-Tuned Model
+
+If users are interested in using a fine-tuned version of stable diffusion, the Python scripts provided in this project can be used to transform a weight dump into a Burn model file. This does not work on Windows.
+
+```bash
+# Step into the Python directory
+cd python
+
+# Download the model, this is just the base v1.4 model as an example
+wget https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
+
+# Install tinygrad
+pip install -r requirements.txt
+
+# Extract the weights
+CPU=1 python3 dump.py sd-v1-4.ckpt
+
+# Move the extracted weight folder out
+mv params ..
+
+# Step out of the Python directory
+cd ..
+
+# Convert the weights into a usable form
+cargo run --release --bin convert params SDv1-4
+```
+
+The binaries 'convert' and 'sample' are contained in Rust. Convert works on CPU whereas sample needs CUDA.
+
+Remember, `convert` should be used if you're planning on using the fine-tuned version of the stable diffusion. 
+
+## License
+
+This project is licensed under MIT license.
+
+We wish you a productive time using this project. Enjoy!