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.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[codz]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py.cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+#poetry.toml
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#   pdm recommends including project-wide configuration in pdm.toml, but excluding .pdm-python.
+#   https://pdm-project.org/en/latest/usage/project/#working-with-version-control
+#pdm.lock
+#pdm.toml
+.pdm-python
+.pdm-build/
+
+# pixi
+#   Similar to Pipfile.lock, it is generally recommended to include pixi.lock in version control.
+#pixi.lock
+#   Pixi creates a virtual environment in the .pixi directory, just like venv module creates one
+#   in the .venv directory. It is recommended not to include this directory in version control.
+.pixi
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.envrc
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
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+# Rope project settings
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+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
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+dmypy.json
+
+# Pyre type checker
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+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Abstra
+# Abstra is an AI-powered process automation framework.
+# Ignore directories containing user credentials, local state, and settings.
+# Learn more at https://abstra.io/docs
+.abstra/
+
+# Visual Studio Code
+#  Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore 
+#  that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
+#  and can be added to the global gitignore or merged into this file. However, if you prefer, 
+#  you could uncomment the following to ignore the entire vscode folder
+# .vscode/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
+
+# Cursor
+#  Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to
+#  exclude from AI features like autocomplete and code analysis. Recommended for sensitive data
+#  refer to https://docs.cursor.com/context/ignore-files
+.cursorignore
+.cursorindexingignore
+
+# Marimo
+marimo/_static/
+marimo/_lsp/
+__marimo__/
+
+# HuggingFace to ModelScope Migration Tool
+# Temporary download directories
+hf2ms_*/
+tmp_*/
+# Token files (never commit tokens!)
+*.token
+tokens.txt
+.tokens
+# Gradio cache and flagged data
+flagged/
+gradio_queue.db

LICENSE

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README.md

@@ -1,14 +1,201 @@
----
-title: Modelscope Migration
-emoji: 😻
-colorFrom: indigo
-colorTo: purple
-sdk: gradio
-sdk_version: 6.2.0
-app_file: app.py
-pinned: false
-license: apache-2.0
-short_description: Migrating to Modelscope
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🚀 HuggingFace to ModelScope Migration Tool
+
+A user-friendly Gradio application for migrating models and datasets from [HuggingFace](https://huggingface.co/) to [ModelScope](https://www.modelscope.cn/).
+
+## ✨ Features
+
+- **Easy Migration**: Migrate models and datasets with a simple web interface
+- **Secure Authentication**: Supports token-based authentication for both platforms
+- **Progress Tracking**: Real-time status updates during migration
+- **Flexible Configuration**: Customize repository visibility, license, and metadata
+- **Error Handling**: Comprehensive error messages and validation
+- **Automatic Cleanup**: Temporary files are automatically cleaned up after migration
+
+## 📋 Prerequisites
+
+- Python 3.8 or higher
+- Internet connection
+- HuggingFace account and access token
+- ModelScope account and SDK token
+
+## 🔧 Installation
+
+1. Clone this repository:
+```bash
+git clone <repository-url>
+cd modelscope-migration
+```
+
+2. Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+Or install manually:
+```bash
+pip install gradio huggingface-hub modelscope
+```
+
+## 🚀 Quick Start
+
+1. Run the application:
+```bash
+python app.py
+```
+
+2. Open your browser and navigate to the provided URL (usually `http://localhost:7860`)
+
+3. Fill in the required information:
+   - **HuggingFace Token**: Get from https://huggingface.co/settings/tokens
+   - **ModelScope Token**: Get from https://www.modelscope.cn/my/myaccesstoken
+   - **Source Repository**: The HuggingFace repository ID (e.g., `bert-base-uncased`)
+   - **Destination Repository**: Your desired ModelScope repository ID (e.g., `username/my-model`)
+
+4. Click "Start Migration" and wait for completion
+
+## 📖 Usage Guide
+
+### Getting Your Tokens
+
+#### HuggingFace Token:
+1. Go to https://huggingface.co/settings/tokens
+2. Click "New token"
+3. Give it a name and select appropriate permissions
+4. Copy the token (starts with `hf_`)
+
+#### ModelScope Token:
+1. Go to https://www.modelscope.cn/my/myaccesstoken
+2. Log in to your account
+3. Copy your SDK token
+
+### Migration Options
+
+| Option | Description | Default |
+|--------|-------------|---------|
+| **Repository Type** | Choose between `model` or `dataset` | `model` |
+| **Visibility** | Set repository as `public` or `private` | `public` |
+| **License** | Choose from Apache 2.0, MIT, GPL-3.0, or Other | `apache-2.0` |
+| **Chinese Name** | Optional Chinese name for the repository | None |
+
+### Example Repository IDs
+
+**HuggingFace:**
+- `bert-base-uncased` (official model)
+- `username/my-custom-model` (user model)
+- `datasets/squad` (dataset)
+
+**ModelScope:**
+- `username/repo-name` (always requires username prefix)
+
+## 🛠️ How It Works
+
+The migration process follows these steps:
+
+1. **Authentication**: Validates tokens for both HuggingFace and ModelScope
+2. **Download**: Uses `snapshot_download` to download the entire repository from HuggingFace
+3. **Upload**: Creates repository on ModelScope (if needed) and uploads all files
+4. **Cleanup**: Removes temporary files from local storage
+
+## 📝 Features in Detail
+
+### Model Migration
+
+Migrates complete model repositories including:
+- Model weights and configuration files
+- Tokenizer files
+- README and documentation
+- Any additional files in the repository
+
+### Dataset Migration
+
+Migrates dataset repositories including:
+- Dataset files (all formats)
+- Dataset cards and metadata
+- Scripts and configuration files
+
+### Error Handling
+
+The tool provides clear error messages for:
+- Invalid tokens
+- Repository not found
+- Permission errors
+- Network issues
+- Disk space problems
+
+## ⚠️ Important Notes
+
+- **Disk Space**: Ensure you have enough disk space for temporary storage of the repository
+- **Large Models**: Migration time depends on repository size and network speed
+- **Permissions**: Your tokens must have appropriate read/write permissions
+- **Private Repos**: To migrate private repositories, ensure your HuggingFace token has access
+- **Repository Creation**: The tool automatically creates the ModelScope repository if it doesn't exist
+
+## 🔒 Security
+
+- Tokens are handled securely and not logged
+- Tokens are entered as password fields (hidden input)
+- Temporary files are cleaned up after migration
+- No data is stored permanently on the server
+
+## 🐛 Troubleshooting
+
+### "Authentication failed"
+- Verify your tokens are correct and not expired
+- Check that you're using the right token for each platform
+
+### "Download failed"
+- Ensure the HuggingFace repository exists and is accessible
+- Check your internet connection
+- Verify you have permission to access the repository
+
+### "Upload failed"
+- Verify your ModelScope token has write permissions
+- Check that the destination repository name is valid
+- Ensure you're not exceeding ModelScope's quotas
+
+### "Disk space error"
+- Free up disk space on your system
+- Large models require significant temporary storage
+
+## 📚 API Documentation
+
+### HuggingFace Hub
+- Documentation: https://huggingface.co/docs/huggingface_hub
+- PyPI: https://pypi.org/project/huggingface-hub/
+
+### ModelScope
+- GitHub: https://github.com/modelscope/modelscope
+- PyPI: https://pypi.org/project/modelscope/
+
+## 🤝 Contributing
+
+Contributions are welcome! Please feel free to submit issues or pull requests.
+
+## 📄 License
+
+This project is open source and available under the Apache 2.0 License.
+
+## 🔗 Resources
+
+- [HuggingFace Hub](https://huggingface.co/)
+- [ModelScope Platform](https://www.modelscope.cn/)
+- [Gradio Documentation](https://gradio.app/docs/)
+
+## 💡 Tips
+
+1. **Test with small models first**: Before migrating large models, test with a smaller repository
+2. **Check licenses**: Ensure you have the right to migrate and redistribute the model/dataset
+3. **Preserve metadata**: The tool preserves all files, but review the ModelScope repository after migration
+4. **Network stability**: For large repositories, ensure a stable internet connection
+
+## 🆘 Support
+
+If you encounter issues:
+1. Check the troubleshooting section above
+2. Review the error message in the status output
+3. Verify your tokens and repository IDs
+4. Check the official documentation for HuggingFace and ModelScope
+
+---
+
+Made with ❤️ using [Gradio](https://gradio.app/), [HuggingFace Hub](https://huggingface.co/), and [ModelScope](https://www.modelscope.cn/)

app.py

@@ -0,0 +1,352 @@
+"""
+HuggingFace to ModelScope Migration Tool
+
+This Gradio app enables migration of models and datasets from HuggingFace to ModelScope.
+"""
+
+import os
+import shutil
+import tempfile
+from pathlib import Path
+from typing import Tuple, Optional
+
+import gradio as gr
+from huggingface_hub import snapshot_download, HfApi
+from modelscope.hub.api import HubApi
+from modelscope.hub.constants import Licenses, ModelVisibility
+
+
+class MigrationTool:
+    """Handles migration of models and datasets between HuggingFace and ModelScope."""
+
+    def __init__(self):
+        self.hf_api = None
+        self.ms_api = None
+        self.temp_dir = None
+
+    def authenticate_hf(self, token: str) -> Tuple[bool, str]:
+        """Authenticate with HuggingFace."""
+        try:
+            self.hf_api = HfApi(token=token)
+            # Test the token
+            self.hf_api.whoami(token=token)
+            return True, "✓ HuggingFace authentication successful"
+        except Exception as e:
+            return False, f"✗ HuggingFace authentication failed: {str(e)}"
+
+    def authenticate_ms(self, token: str) -> Tuple[bool, str]:
+        """Authenticate with ModelScope."""
+        try:
+            self.ms_api = HubApi()
+            self.ms_api.login(token)
+            return True, "✓ ModelScope authentication successful"
+        except Exception as e:
+            return False, f"✗ ModelScope authentication failed: {str(e)}"
+
+    def download_from_hf(
+        self,
+        repo_id: str,
+        repo_type: str = "model"
+    ) -> Tuple[bool, str, Optional[str]]:
+        """Download a repository from HuggingFace.
+
+        Args:
+            repo_id: HuggingFace repository ID (e.g., 'username/repo-name')
+            repo_type: Type of repository ('model' or 'dataset')
+
+        Returns:
+            Tuple of (success, message, local_path)
+        """
+        try:
+            # Create temporary directory
+            self.temp_dir = tempfile.mkdtemp(prefix="hf2ms_")
+
+            # Download the repository
+            local_path = snapshot_download(
+                repo_id=repo_id,
+                repo_type=repo_type,
+                local_dir=self.temp_dir,
+                local_dir_use_symlinks=False,
+                token=self.hf_api.token if self.hf_api else None
+            )
+
+            return True, f"✓ Successfully downloaded {repo_type} from HuggingFace", local_path
+        except Exception as e:
+            return False, f"✗ Download failed: {str(e)}", None
+
+    def upload_to_ms(
+        self,
+        local_path: str,
+        repo_id: str,
+        repo_type: str = "model",
+        visibility: str = "public",
+        license_type: str = "apache-2.0",
+        chinese_name: Optional[str] = None
+    ) -> Tuple[bool, str]:
+        """Upload a repository to ModelScope.
+
+        Args:
+            local_path: Local path to the repository
+            repo_id: ModelScope repository ID (e.g., 'username/repo-name')
+            repo_type: Type of repository ('model' or 'dataset')
+            visibility: Repository visibility ('public' or 'private')
+            license_type: License type
+            chinese_name: Optional Chinese name for the repository
+
+        Returns:
+            Tuple of (success, message)
+        """
+        try:
+            if not self.ms_api:
+                return False, "✗ ModelScope not authenticated"
+
+            # Determine visibility
+            vis = ModelVisibility.PUBLIC if visibility == "public" else ModelVisibility.PRIVATE
+
+            # Map license types
+            license_map = {
+                "apache-2.0": Licenses.APACHE_V2,
+                "mit": Licenses.MIT,
+                "gpl-3.0": Licenses.GPL_V3,
+                "other": Licenses.OTHER,
+            }
+            lic = license_map.get(license_type.lower(), Licenses.APACHE_V2)
+
+            # Create repository if it doesn't exist
+            try:
+                if repo_type == "model":
+                    self.ms_api.create_model(
+                        model_id=repo_id,
+                        visibility=vis,
+                        license=lic,
+                        chinese_name=chinese_name
+                    )
+            except Exception as create_error:
+                # Repository might already exist, continue to push
+                pass
+
+            # Push the model/dataset
+            if repo_type == "model":
+                self.ms_api.push_model(
+                    model_id=repo_id,
+                    model_dir=local_path
+                )
+            else:
+                # For datasets, use similar approach
+                self.ms_api.push_model(
+                    model_id=repo_id,
+                    model_dir=local_path
+                )
+
+            return True, f"✓ Successfully uploaded {repo_type} to ModelScope"
+        except Exception as e:
+            return False, f"✗ Upload failed: {str(e)}"
+
+    def cleanup(self):
+        """Clean up temporary files."""
+        if self.temp_dir and os.path.exists(self.temp_dir):
+            try:
+                shutil.rmtree(self.temp_dir)
+                self.temp_dir = None
+            except Exception as e:
+                print(f"Warning: Failed to clean up temporary directory: {e}")
+
+    def migrate(
+        self,
+        hf_token: str,
+        ms_token: str,
+        hf_repo_id: str,
+        ms_repo_id: str,
+        repo_type: str,
+        visibility: str,
+        license_type: str,
+        chinese_name: Optional[str] = None
+    ) -> str:
+        """Perform the complete migration process.
+
+        Returns:
+            Status message with migration progress
+        """
+        output = []
+
+        # Validate inputs
+        if not hf_token or not ms_token:
+            return "✗ Error: Both HuggingFace and ModelScope tokens are required"
+
+        if not hf_repo_id or not ms_repo_id:
+            return "✗ Error: Both source and destination repository IDs are required"
+
+        # Authenticate with HuggingFace
+        output.append("🔐 Authenticating with HuggingFace...")
+        success, msg = self.authenticate_hf(hf_token)
+        output.append(msg)
+        if not success:
+            return "\n".join(output)
+
+        # Authenticate with ModelScope
+        output.append("\n🔐 Authenticating with ModelScope...")
+        success, msg = self.authenticate_ms(ms_token)
+        output.append(msg)
+        if not success:
+            return "\n".join(output)
+
+        # Download from HuggingFace
+        output.append(f"\n⬇️  Downloading {repo_type} from HuggingFace: {hf_repo_id}...")
+        success, msg, local_path = self.download_from_hf(hf_repo_id, repo_type)
+        output.append(msg)
+        if not success:
+            self.cleanup()
+            return "\n".join(output)
+
+        # Upload to ModelScope
+        output.append(f"\n⬆️  Uploading {repo_type} to ModelScope: {ms_repo_id}...")
+        success, msg = self.upload_to_ms(
+            local_path,
+            ms_repo_id,
+            repo_type,
+            visibility,
+            license_type,
+            chinese_name
+        )
+        output.append(msg)
+
+        # Cleanup
+        output.append("\n🧹 Cleaning up temporary files...")
+        self.cleanup()
+        output.append("✓ Cleanup complete")
+
+        if success:
+            output.append(f"\n✅ Migration completed successfully!")
+            output.append(f"Your {repo_type} is now available at: https://www.modelscope.cn/models/{ms_repo_id}")
+        else:
+            output.append(f"\n❌ Migration failed")
+
+        return "\n".join(output)
+
+
+def create_interface():
+    """Create the Gradio interface."""
+
+    migration_tool = MigrationTool()
+
+    with gr.Blocks(title="HuggingFace to ModelScope Migration Tool") as app:
+        gr.Markdown("""
+        # 🚀 HuggingFace to ModelScope Migration Tool
+
+        Easily migrate your models and datasets from HuggingFace to ModelScope.
+
+        ## 📋 Instructions:
+        1. Get your **HuggingFace token** from: https://huggingface.co/settings/tokens
+        2. Get your **ModelScope token** from: https://www.modelscope.cn/my/myaccesstoken
+        3. Fill in the repository details below
+        4. Click "Start Migration"
+        """)
+
+        with gr.Row():
+            with gr.Column():
+                gr.Markdown("### 🔑 Authentication")
+                hf_token = gr.Textbox(
+                    label="HuggingFace Token",
+                    type="password",
+                    placeholder="hf_...",
+                    info="Your HuggingFace access token"
+                )
+                ms_token = gr.Textbox(
+                    label="ModelScope Token",
+                    type="password",
+                    placeholder="Enter your ModelScope token",
+                    info="Your ModelScope SDK token"
+                )
+
+            with gr.Column():
+                gr.Markdown("### 📦 Repository Details")
+                repo_type = gr.Radio(
+                    choices=["model", "dataset"],
+                    label="Repository Type",
+                    value="model",
+                    info="Select what you want to migrate"
+                )
+                visibility = gr.Radio(
+                    choices=["public", "private"],
+                    label="Visibility",
+                    value="public",
+                    info="Visibility of the repository on ModelScope"
+                )
+
+        with gr.Row():
+            with gr.Column():
+                hf_repo_id = gr.Textbox(
+                    label="Source HuggingFace Repo ID",
+                    placeholder="username/repo-name",
+                    info="e.g., bert-base-uncased or username/my-model"
+                )
+
+            with gr.Column():
+                ms_repo_id = gr.Textbox(
+                    label="Destination ModelScope Repo ID",
+                    placeholder="username/repo-name",
+                    info="Your ModelScope username/repo-name"
+                )
+
+        with gr.Row():
+            with gr.Column():
+                license_type = gr.Dropdown(
+                    choices=["apache-2.0", "mit", "gpl-3.0", "other"],
+                    label="License",
+                    value="apache-2.0",
+                    info="License for the repository"
+                )
+
+            with gr.Column():
+                chinese_name = gr.Textbox(
+                    label="Chinese Name (Optional)",
+                    placeholder="模型中文名称",
+                    info="Optional Chinese name for the repository"
+                )
+
+        migrate_btn = gr.Button("🚀 Start Migration", variant="primary", size="lg")
+
+        output = gr.Textbox(
+            label="Migration Status",
+            lines=15,
+            max_lines=20,
+            interactive=False,
+            show_copy_button=True
+        )
+
+        migrate_btn.click(
+            fn=migration_tool.migrate,
+            inputs=[
+                hf_token,
+                ms_token,
+                hf_repo_id,
+                ms_repo_id,
+                repo_type,
+                visibility,
+                license_type,
+                chinese_name
+            ],
+            outputs=output
+        )
+
+        gr.Markdown("""
+        ---
+        ### 📝 Notes:
+        - Large models may take some time to download and upload
+        - Make sure you have enough disk space for temporary storage
+        - Private repositories require appropriate token permissions
+        - The tool will create the repository on ModelScope if it doesn't exist
+
+        ### 🔗 Resources:
+        - [HuggingFace Hub](https://huggingface.co/)
+        - [ModelScope](https://www.modelscope.cn/)
+        - [HuggingFace Token Settings](https://huggingface.co/settings/tokens)
+        - [ModelScope Token Settings](https://www.modelscope.cn/my/myaccesstoken)
+        """)
+
+    return app
+
+
+if __name__ == "__main__":
+    app = create_interface()
+    app.launch(share=False)

example_usage.py

@@ -0,0 +1,73 @@
+"""
+Example script demonstrating programmatic usage of the HuggingFace to ModelScope Migration Tool.
+
+This example shows how to use the MigrationTool class directly without the Gradio UI.
+"""
+
+import os
+from app import MigrationTool
+
+
+def main():
+    """Example migration workflow."""
+
+    # Initialize the migration tool
+    tool = MigrationTool()
+
+    # Configuration - Replace these with your actual values
+    # IMPORTANT: Never hardcode tokens in production code!
+    # Use environment variables or secure credential management instead.
+    HF_TOKEN = os.getenv("HUGGINGFACE_TOKEN", "")
+    MS_TOKEN = os.getenv("MODELSCOPE_TOKEN", "")
+
+    # Source repository on HuggingFace
+    HF_REPO_ID = "sentence-transformers/all-MiniLM-L6-v2"  # Example small model
+
+    # Destination repository on ModelScope
+    MS_REPO_ID = "your-username/all-MiniLM-L6-v2"  # Replace with your repo
+
+    # Repository configuration
+    REPO_TYPE = "model"  # or "dataset"
+    VISIBILITY = "public"  # or "private"
+    LICENSE = "apache-2.0"  # apache-2.0, mit, gpl-3.0, other
+    CHINESE_NAME = "小型句子转换模型"  # Optional
+
+    # Validate tokens
+    if not HF_TOKEN or not MS_TOKEN:
+        print("Error: Please set HUGGINGFACE_TOKEN and MODELSCOPE_TOKEN environment variables")
+        print("\nExample:")
+        print("  export HUGGINGFACE_TOKEN='hf_...'")
+        print("  export MODELSCOPE_TOKEN='your-token'")
+        print("  python example_usage.py")
+        return
+
+    print("=" * 60)
+    print("HuggingFace to ModelScope Migration Tool - Example Usage")
+    print("=" * 60)
+    print()
+    print(f"Source: {HF_REPO_ID}")
+    print(f"Destination: {MS_REPO_ID}")
+    print(f"Type: {REPO_TYPE}")
+    print(f"Visibility: {VISIBILITY}")
+    print()
+
+    # Perform the migration
+    result = tool.migrate(
+        hf_token=HF_TOKEN,
+        ms_token=MS_TOKEN,
+        hf_repo_id=HF_REPO_ID,
+        ms_repo_id=MS_REPO_ID,
+        repo_type=REPO_TYPE,
+        visibility=VISIBILITY,
+        license_type=LICENSE,
+        chinese_name=CHINESE_NAME
+    )
+
+    # Print the result
+    print(result)
+    print()
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -0,0 +1,3 @@
+gradio>=4.0.0
+huggingface-hub>=0.20.0
+modelscope>=1.11.0