Clean up: Remove unnecessary guide files, keep only essential model files

CHECKLIST.md

@@ -1,185 +0,0 @@
-# Pre-Upload Checklist ✅
-
-## Before You Upload
-
-### 1. Files Ready
-- [x] README.md (comprehensive model card)
-- [x] config.json (model configuration)
-- [x] requirements.txt (dependencies)
-- [x] inference.py (inference script)
-- [x] example_usage.py (usage examples)
-- [x] .gitattributes (Git LFS config)
-- [x] best_model_finetuned.pth (main model - 43MB)
-- [x] best_model_simple.pth (alternative model - 2.4MB)
-- [x] Marine 1.mlmodel (CoreML model - 13KB)
-
-### 2. Prerequisites Installed
-- [ ] Hugging Face CLI: `pip install huggingface_hub`
-- [ ] Git LFS: `brew install git-lfs` (macOS) or `sudo apt-get install git-lfs` (Linux)
-- [ ] Git LFS initialized: `git lfs install`
-
-### 3. Authentication
-- [ ] Hugging Face account created at https://huggingface.co
-- [ ] Access token generated at https://huggingface.co/settings/tokens
-- [ ] Logged in: `huggingface-cli login`
-- [ ] Verify login: `huggingface-cli whoami`
-
-### 4. Repository Setup
-- [ ] Repository created at https://huggingface.co/new
-- [ ] Repository name: `shiv207/Marine1`
-- [ ] Repository type: Model
-- [ ] License: MIT
-
-### 5. Testing
-- [ ] Test inference script locally:
-  ```bash
-  cd huggingface
-  python inference.py best_model_finetuned.pth ../path/to/test/audio.wav
-  ```
-- [ ] Verify all model files load correctly
-- [ ] Check file sizes are reasonable
-
-### 6. Documentation Quality
-- [ ] README has clear description
-- [ ] Usage examples are included
-- [ ] Limitations are documented
-- [ ] Citation information is provided
-- [ ] Contact information is included
-- [ ] License is specified
-
-## Upload Methods
-
-### Method 1: Quick Upload (Recommended for First Time)
-```bash
-cd huggingface
-./upload.sh
-```
-
-### Method 2: Manual CLI Upload
-```bash
-cd huggingface
-huggingface-cli upload shiv207/Marine1 . --repo-type model
-```
-
-### Method 3: Git Method (More Control)
-```bash
-# Clone repository
-git clone https://huggingface.co/shiv207/Marine1
-cd Marine1
-
-# Copy files
-cp ../huggingface/* .
-
-# Setup Git LFS
-git lfs track "*.pth"
-git lfs track "*.mlmodel"
-
-# Commit and push
-git add .
-git commit -m "Initial upload: Marine1 Underwater Acoustic Classifier"
-git push
-```
-
-## After Upload
-
-### Immediate Checks
-- [ ] Visit https://huggingface.co/shiv207/Marine1
-- [ ] Verify README renders correctly
-- [ ] Check all files are uploaded
-- [ ] Verify file sizes (should show actual size, not pointer)
-- [ ] Test model download:
-  ```python
-  from huggingface_hub import hf_hub_download
-  model_path = hf_hub_download(repo_id="shiv207/Marine1", filename="best_model_finetuned.pth")
-  ```
-
-### Repository Settings
-- [ ] Set visibility to Public
-- [ ] Verify license is MIT
-- [ ] Check tags are correct
-- [ ] Add repository description
-- [ ] Add topics/keywords
-
-### Documentation
-- [ ] README displays properly
-- [ ] Code blocks are formatted
-- [ ] Links work correctly
-- [ ] Images load (if any)
-- [ ] Metadata is parsed correctly
-
-### Testing
-- [ ] Download model using HF Hub
-- [ ] Run inference with downloaded model
-- [ ] Verify predictions are correct
-- [ ] Test on different audio files
-
-## Promotion (Optional)
-
-### Share Your Model
-- [ ] Tweet about it with #HuggingFace #MarineAI #UnderwaterAcoustics
-- [ ] Post on LinkedIn
-- [ ] Share in Hugging Face Discord
-- [ ] Add to your GitHub README
-- [ ] Post in relevant Reddit communities (r/MachineLearning, r/oceanography)
-
-### Documentation
-- [ ] Write a blog post on Hugging Face
-- [ ] Create a demo video
-- [ ] Add to Papers with Code (if applicable)
-- [ ] Update your portfolio/website
-
-### Community
-- [ ] Respond to issues and questions
-- [ ] Accept pull requests for improvements
-- [ ] Update model based on feedback
-- [ ] Add more examples and tutorials
-
-## Troubleshooting
-
-### Common Issues
-
-**Large File Upload Fails**
-```bash
-git lfs track "*.pth"
-git add .gitattributes
-git add *.pth
-git commit --amend
-git push --force
-```
-
-**Authentication Error**
-```bash
-huggingface-cli logout
-huggingface-cli login
-```
-
-**Model Not Found After Upload**
-- Wait a few minutes for processing
-- Check repository visibility settings
-- Verify file was uploaded (not just LFS pointer)
-
-**README Not Rendering**
-- Check YAML frontmatter syntax
-- Verify markdown formatting
-- Look for special characters that need escaping
-
-## Support Resources
-
-- Hugging Face Docs: https://huggingface.co/docs
-- Model Hub Guide: https://huggingface.co/docs/hub/models
-- Git LFS Guide: https://git-lfs.github.com
-- Community Forum: https://discuss.huggingface.co
-- Discord: https://hf.co/join/discord
-
-## Final Notes
-
-- First upload may take 10-15 minutes depending on file sizes
-- Model will be publicly accessible immediately after upload
-- You can update files anytime using the same upload commands
-- Consider adding a demo Space later for interactive testing
-
----
-
-**Ready to upload?** Run `./upload.sh` from the huggingface directory!
-
-Good luck with your first Hugging Face model! 🎉🌊

QUICK_START.md

@@ -1,87 +0,0 @@
-# Quick Start Guide 🚀
-
-## Upload in 3 Steps
-
-### Step 1: Install & Login
-```bash
-# Install Hugging Face CLI
-pip install huggingface_hub
-
-# Install Git LFS (for large files)
-brew install git-lfs  # macOS
-# or: sudo apt-get install git-lfs  # Linux
-
-# Initialize Git LFS
-git lfs install
-
-# Login to Hugging Face
-huggingface-cli login
-# Paste your token from: https://huggingface.co/settings/tokens
-```
-
-### Step 2: Create Repository
-1. Go to https://huggingface.co/new
-2. Repository name: `Marine1`
-3. Owner: `shiv207`
-4. Type: Model
-5. License: MIT
-6. Click "Create model"
-
-### Step 3: Upload
-```bash
-cd huggingface
-./upload.sh
-```
-
-That's it! Your model will be live at: https://huggingface.co/shiv207/Marine1
-
-## What Gets Uploaded
-
-✅ **3 Model Files:**
-- `best_model_finetuned.pth` - Fine-tuned ResNet18 (98.33% accuracy) - 43MB
-- `best_model_simple.pth` - Simple CNN (93% accuracy) - 2.4MB  
-- `Marine 1.mlmodel` - CoreML for iOS/macOS - 13KB
-
-✅ **Documentation:**
-- `README.md` - Comprehensive model card
-- `config.json` - Model configuration
-- `requirements.txt` - Dependencies
-
-✅ **Code Examples:**
-- `inference.py` - Ready-to-use inference script
-- `example_usage.py` - Usage examples
-
-## After Upload
-
-### Test Your Model
-```python
-from huggingface_hub import hf_hub_download
-
-# Download model
-model_path = hf_hub_download(
-    repo_id="shiv207/Marine1",
-    filename="best_model_finetuned.pth"
-)
-
-# Use it
-from inference import Marine1Classifier
-classifier = Marine1Classifier(model_path)
-result = classifier.predict("audio.wav")
-print(result)
-```
-
-### Share It
-- Tweet: "Just uploaded my first model to @huggingface! 🌊 Marine1 classifies underwater sounds with 98% accuracy. Check it out: https://huggingface.co/shiv207/Marine1 #MachineLearning #MarineAI"
-- LinkedIn: Share your achievement
-- GitHub: Add badge to README
-
-## Need Help?
-
-- 📖 Full guide: See `UPLOAD_GUIDE.md`
-- ✅ Checklist: See `CHECKLIST.md`
-- 💬 Questions: https://discuss.huggingface.co
-- 🐛 Issues: https://github.com/shiv207/underwater-audio-classifier/issues
-
----
-
-**Ready?** Just run `./upload.sh` and you're done! 🎉

UPLOAD_GUIDE.md

@@ -1,208 +0,0 @@
-# Hugging Face Upload Guide for Marine1 🚀
-
-## Prerequisites
-
-1. **Install Hugging Face CLI**
-```bash
-pip install huggingface_hub
-```
-
-2. **Login to Hugging Face**
-```bash
-huggingface-cli login
-```
-Enter your Hugging Face token when prompted. Get your token from: https://huggingface.co/settings/tokens
-
-3. **Install Git LFS** (for large files)
-```bash
-# macOS
-brew install git-lfs
-
-# Ubuntu/Debian
-sudo apt-get install git-lfs
-
-# Initialize Git LFS
-git lfs install
-```
-
-## Upload Steps
-
-### Option 1: Using Hugging Face CLI (Recommended)
-
-```bash
-# Navigate to the huggingface directory
-cd huggingface
-
-# Upload all files to your model repository
-huggingface-cli upload shiv207/Marine1 . --repo-type model
-```
-
-### Option 2: Using Git (More Control)
-
-```bash
-# Clone your model repository (create it first on huggingface.co)
-git clone https://huggingface.co/shiv207/Marine1
-cd Marine1
-
-# Copy all files from the huggingface directory
-cp ../huggingface/* .
-
-# Track large files with Git LFS
-git lfs track "*.pth"
-git lfs track "*.mlmodel"
-
-# Add and commit files
-git add .
-git commit -m "Initial upload: Marine1 Underwater Acoustic Classifier"
-
-# Push to Hugging Face
-git push
-```
-
-### Option 3: Using Python API
-
-```python
-from huggingface_hub import HfApi
-
-api = HfApi()
-
-# Upload all files
-api.upload_folder(
-    folder_path="./huggingface",
-    repo_id="shiv207/Marine1",
-    repo_type="model",
-)
-```
-
-## Files to Upload
-
-Make sure these files are in your huggingface directory:
-
-- ✅ `README.md` - Model card with documentation
-- ✅ `config.json` - Model configuration
-- ✅ `requirements.txt` - Dependencies
-- ✅ `inference.py` - Example inference script
-- ✅ `.gitattributes` - Git LFS configuration
-- ✅ `best_model_finetuned.pth` - Fine-tuned model (98.33% accuracy)
-- ✅ `best_model_simple.pth` - Simple CNN model (93% accuracy)
-- ✅ `Marine 1.mlmodel` - CoreML model for iOS/macOS
-
-## Before Uploading
-
-1. **Copy model files to huggingface directory:**
-```bash
-cp models/best_model_finetuned.pth huggingface/
-cp models/best_model_simple.pth huggingface/
-cp models/Marine\ 1.mlmodel huggingface/
-```
-
-2. **Test the inference script:**
-```bash
-cd huggingface
-python inference.py best_model_finetuned.pth ../path/to/test/audio.wav
-```
-
-3. **Verify all files are present:**
-```bash
-ls -lh huggingface/
-```
-
-## Post-Upload Checklist
-
-After uploading, verify on Hugging Face:
-
-- [ ] Model card displays correctly
-- [ ] All three model files are uploaded
-- [ ] Files are tracked with Git LFS (check file sizes)
-- [ ] README renders properly with metadata
-- [ ] Model appears in search results
-- [ ] Tags are correct (audio-classification, underwater-acoustics, etc.)
-
-## Model Repository Settings
-
-On huggingface.co/shiv207/Marine1/settings:
-
-1. **Visibility**: Public (recommended for first model)
-2. **License**: MIT
-3. **Tags**: Already set in README.md frontmatter
-4. **Widget**: Disable (audio classification widget not fully supported yet)
-
-## Updating the Model
-
-To update files later:
-
-```bash
-# Using CLI
-huggingface-cli upload shiv207/Marine1 ./updated_file.pth
-
-# Or using Git
-cd Marine1
-git pull
-# Make changes
-git add .
-git commit -m "Update: description of changes"
-git push
-```
-
-## Troubleshooting
-
-### Large File Issues
-If you get errors about file size:
-```bash
-git lfs track "*.pth"
-git add .gitattributes
-git add *.pth
-git commit -m "Track large files with LFS"
-```
-
-### Authentication Issues
-```bash
-# Re-login
-huggingface-cli login --token YOUR_TOKEN
-```
-
-### Upload Timeout
-For large files, increase timeout:
-```bash
-export HF_HUB_TIMEOUT=300
-huggingface-cli upload shiv207/Marine1 . --repo-type model
-```
-
-## Example Usage After Upload
-
-Users can then use your model like this:
-
-```python
-from huggingface_hub import hf_hub_download
-
-# Download model
-model_path = hf_hub_download(
-    repo_id="shiv207/Marine1",
-    filename="best_model_finetuned.pth"
-)
-
-# Use with your inference script
-from inference import Marine1Classifier
-classifier = Marine1Classifier(model_path)
-result = classifier.predict("audio.wav")
-```
-
-## Promotion Tips
-
-After uploading:
-
-1. Share on Twitter/LinkedIn with #HuggingFace #MarineAI
-2. Post in Hugging Face Discord community
-3. Add to your GitHub README
-4. Consider writing a blog post on Hugging Face blog
-5. Add to Papers with Code if you have a paper
-
-## Support
-
-- Hugging Face Docs: https://huggingface.co/docs
-- Community Forum: https://discuss.huggingface.co
-- Discord: https://hf.co/join/discord
-
----
-
-Good luck with your first Hugging Face model upload! 🎉

model_card_metadata.yml

@@ -1,52 +0,0 @@
-# Model Card Metadata for Marine1
-# This file contains structured metadata for better discoverability
-
-language: en
-license: mit
-library_name: pytorch
-tags:
-  - audio
-  - audio-classification
-  - underwater-acoustics
-  - marine-biology
-  - oceanography
-  - conservation
-  - pytorch
-  - resnet18
-  - transfer-learning
-  - mel-spectrogram
-  - marine-mammals
-  - vessel-detection
-  - environmental-monitoring
-
-datasets:
-  - custom
-
-metrics:
-  - accuracy
-  - balanced_accuracy
-
-model-index:
-  - name: Marine1-Underwater-Acoustic-Classifier
-    results:
-      - task:
-          type: audio-classification
-          name: Underwater Sound Classification
-        dataset:
-          name: Custom Underwater Acoustics Dataset
-          type: custom
-        metrics:
-          - type: accuracy
-            value: 98.33
-            name: Test Accuracy
-          - type: balanced_accuracy
-            value: 91.67
-            name: Balanced Accuracy
-
-pipeline_tag: audio-classification
-
-widget:
-  - example_title: Marine Animal Sound
-    src: https://example.com/whale.wav
-  - example_title: Vessel Sound
-    src: https://example.com/ship.wav

upload.sh

@@ -1,73 +0,0 @@
-#!/bin/bash
-
-# Marine1 Hugging Face Upload Script
-# This script uploads your model to Hugging Face Hub
-
-set -e  # Exit on error
-
-echo "🌊 Marine1 Hugging Face Upload Script"
-echo "======================================"
-echo ""
-
-# Check if huggingface-cli is installed
-if ! command -v huggingface-cli &> /dev/null; then
-    echo "❌ huggingface-cli not found!"
-    echo "Install it with: pip install huggingface_hub"
-    exit 1
-fi
-
-# Check if user is logged in
-if ! huggingface-cli whoami &> /dev/null; then
-    echo "❌ Not logged in to Hugging Face!"
-    echo "Login with: huggingface-cli login"
-    exit 1
-fi
-
-echo "✅ Hugging Face CLI found and authenticated"
-echo ""
-
-# Check if Git LFS is installed
-if ! command -v git-lfs &> /dev/null; then
-    echo "⚠️  Warning: Git LFS not found!"
-    echo "Large files may fail to upload."
-    echo "Install with: brew install git-lfs (macOS) or sudo apt-get install git-lfs (Linux)"
-    echo ""
-    read -p "Continue anyway? (y/n) " -n 1 -r
-    echo
-    if [[ ! $REPLY =~ ^[Yy]$ ]]; then
-        exit 1
-    fi
-else
-    echo "✅ Git LFS found"
-fi
-
-echo ""
-echo "Files to upload:"
-ls -lh *.pth *.mlmodel 2>/dev/null || echo "  (model files)"
-echo ""
-
-# Confirm upload
-read -p "Upload to shiv207/Marine1? (y/n) " -n 1 -r
-echo
-if [[ ! $REPLY =~ ^[Yy]$ ]]; then
-    echo "Upload cancelled."
-    exit 0
-fi
-
-echo ""
-echo "🚀 Starting upload..."
-echo ""
-
-# Upload using huggingface-cli
-huggingface-cli upload shiv207/Marine1 . --repo-type model
-
-echo ""
-echo "✅ Upload complete!"
-echo ""
-echo "View your model at: https://huggingface.co/shiv207/Marine1"
-echo ""
-echo "Next steps:"
-echo "  1. Visit the model page and verify everything looks good"
-echo "  2. Test downloading and using the model"
-echo "  3. Share your model with the community!"
-echo ""