Upload QUICK_REFERENCE.md with huggingface_hub

QUICK_REFERENCE.md

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+# Quick Reference - Hugging Face Integration
+
+## Upload Model to HF Hub
+
+### Option 1: Interactive (Easiest)
+```bash
+python publish_to_hf.py
+# Enter token when prompted
+# Enter repo_id when prompted (e.g., Enzo8930302/ByteDream)
+```
+
+### Option 2: Command Line
+```bash
+python publish_to_hf.py hf_xxxxxxxxxxxxx Enzo8930302/ByteDream
+```
+
+### Option 3: Python Code
+```python
+from bytedream import ByteDreamGenerator
+
+generator = ByteDreamGenerator(model_path="./models/bytedream")
+generator.push_to_hub(
+    repo_id="Enzo8930302/ByteDream",
+    token="hf_xxxxx"
+)
+```
+
+---
+
+## Load Model from HF Hub
+
+### Python - Generator
+```python
+from bytedream import ByteDreamGenerator
+
+generator = ByteDreamGenerator(hf_repo_id="Enzo8930302/ByteDream")
+image = generator.generate("Your prompt")
+image.save("output.png")
+```
+
+### Python - Pipeline
+```python
+from bytedream.pipeline import ByteDreamPipeline
+
+pipeline = ByteDreamPipeline.from_pretrained("Enzo8930302/ByteDream")
+result = pipeline("Your prompt")
+result[0].save("output.png")
+```
+
+### Command Line
+```bash
+python infer.py --prompt "Dragon flying" --hf_repo "Enzo8930302/ByteDream" --output dragon.png
+```
+
+### Web Interface
+```bash
+# Set environment variable
+export HF_REPO_ID=Enzo8930302/ByteDream
+
+# Run app
+python app.py
+```
+
+---
+
+## Deploy to Hugging Face Spaces
+
+1. **Create Space**: https://huggingface.co/spaces → Create new Space
+2. **Choose**: Gradio SDK + CPU Basic
+3. **Push files**:
+   ```bash
+   git clone https://huggingface.co/spaces/YOUR_USERNAME/SPACE_NAME
+   cp -r ../Byte\ Dream/* SPACE_NAME/
+   cd SPACE_NAME
+   git add .
+   git commit -m "Deploy Byte Dream"
+   git push
+   ```
+4. **Set env var**: In Space settings → Add `HF_REPO_ID=Enzo8930302/ByteDream`
+5. **Done!** Available at: `https://huggingface.co/spaces/YOUR_USERNAME/SPACE_NAME`
+
+---
+
+## Common Commands
+
+### Get HF Token
+- Go to: https://huggingface.co/settings/tokens
+- Click "New token"
+- Copy token (starts with `hf_`)
+
+### Check Model Exists
+```bash
+# List files in your HF repo
+huggingface-cli ls Enzo8930302/ByteDream
+```
+
+### Download Model Manually
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download(repo_id="Enzo8930302/ByteDream")
+```
+
+### Test Installation
+```bash
+python -c "from huggingface_hub import login; print('OK')"
+```
+
+---
+
+## Environment Variables
+
+```bash
+# Load model from HF in app.py
+export HF_REPO_ID=Enzo8930302/ByteDream
+
+# Custom model path
+export MODEL_PATH=./models/bytedream
+
+# Set HF cache directory
+export HF_HOME=~/.cache/huggingface
+```
+
+---
+
+## Example Prompts
+
+```python
+prompts = [
+    "A beautiful sunset over mountains, digital art",
+    "Cyberpunk city at night, neon lights, futuristic",
+    "Fantasy dragon breathing fire, dramatic lighting",
+    "Peaceful cottage in meadow, flowers, sunny day",
+    "Underwater coral reef, tropical fish, sunlight",
+    "Abstract geometric art, colorful shapes, modern",
+]
+
+from bytedream import ByteDreamGenerator
+generator = ByteDreamGenerator(hf_repo_id="Enzo8930302/ByteDream")
+
+for i, prompt in enumerate(prompts):
+    image = generator.generate(prompt, num_inference_steps=50)
+    image.save(f"image_{i}.png")
+```
+
+---
+
+## Troubleshooting Quick Fixes
+
+**Error: Repository not found**
+```python
+# Make repo public or provide token
+from huggingface_hub import login
+login(token="hf_xxxxx")
+```
+
+**Error: Out of memory**
+```python
+# Reduce size
+generator.generate(width=256, height=256)
+# Fewer steps
+generator.generate(num_inference_steps=20)
+```
+
+**Error: Model not trained**
+```bash
+# Train first
+python train.py
+# Or download from HF
+python infer.py --hf_repo username/model --prompt "test"
+```
+
+---
+
+## File Structure on HF
+
+```
+username/ByteDream/
+├── unet/
+│   └── pytorch_model.bin
+├── vae/
+│   └── pytorch_model.bin
+├── scheduler/
+│   └── scheduler_config.json
+├── model_index.json
+├── config.yaml
+└── README.md
+```
+
+---
+
+## API Methods Summary
+
+### ByteDreamGenerator
+```python
+# Initialize with HF model
+ByteDreamGenerator(hf_repo_id="username/repo")
+
+# Upload to HF
+generator.push_to_hub(repo_id="username/repo", token="hf_xxx")
+
+# Save locally
+generator.save_pretrained("./models/bytedream")
+```
+
+### ByteDreamPipeline
+```python
+# Load from HF
+pipeline = ByteDreamPipeline.from_pretrained("username/repo")
+
+# Load from local
+pipeline = ByteDreamPipeline.from_pretrained("./models/bytedream")
+
+# Save to HF
+pipeline.save_pretrained("./models/bytedream")
+```
+
+---
+
+## Complete Workflow Example
+
+```python
+# 1. Train (if needed)
+# python train.py
+
+# 2. Load model
+from bytedream import ByteDreamGenerator
+generator = ByteDreamGenerator(model_path="./models/bytedream")
+
+# 3. Test generation
+image = generator.generate("Test prompt")
+image.save("test.png")
+
+# 4. Upload to HF
+generator.push_to_hub(
+    repo_id="Enzo8930302/ByteDream",
+    token="hf_xxxxxxxx"
+)
+
+print("✓ Uploaded to HF!")
+
+# 5. Use from HF (new session)
+generator2 = ByteDreamGenerator(hf_repo_id="Enzo8930302/ByteDream")
+image2 = generator2.generate("Amazing prompt")
+image2.save("amazing.png")
+```
+
+---
+
+**More Info**: See `HF_INTEGRATION_GUIDE.md` for detailed documentation