🌳 Model Family Tree
Automatically calculate the family tree of a given model. It also displays the type of license each model uses (permissive, noncommercial, or unknown).
You can also run the code in this Colab notebook.
""" def get_model_names_from_yaml(url): """Get a list of parent model names from the yaml file.""" model_tags = [] response = requests.get(url) if response.status_code == 200: model_tags.extend([item for item in response.content if '/' in str(item)]) return model_tags def get_license_color(model): """Get the color of the model based on its license.""" try: card = ModelCard.load(model) license = card.data.to_dict()['license'].lower() # Define permissive licenses permissive_licenses = ['mit', 'bsd', 'apache-2.0', 'openrail'] # Add more as needed # Check license type if any(perm_license in license for perm_license in permissive_licenses): return 'lightgreen' # Permissive licenses else: return 'lightcoral' # Noncommercial or other licenses except Exception as e: print(f"Error retrieving license for {model}: {e}") return 'lightgray' def get_model_names(model, genealogy, found_models=None): """Get a list of parent model names from the model id.""" model_tags = [] if found_models is None: found_models = [] try: card = ModelCard.load(model) card_dict = card.data.to_dict() # Convert the ModelCard object to a dictionary license = card_dict['license'] # Check the base_model in metadata if 'base_model' in card_dict: model_tags = card_dict['base_model'] # Check the tags in metadata if 'tags' in card_dict and not model_tags: tags = card_dict['tags'] model_tags = [model_name for model_name in tags if '/' in model_name] # Check for merge.yml and mergekit_config.yml if no model_tags found in the tags if not model_tags: model_tags.extend(get_model_names_from_yaml(f"https://huggingface.co/{model}/blob/main/merge.yml")) if not model_tags: model_tags.extend(get_model_names_from_yaml(f"https://huggingface.co/{model}/blob/main/mergekit_config.yml")) # Convert to a list if tags is not None or empty, else set to an empty list if not isinstance(model_tags, list): model_tags = [model_tags] if model_tags else [] # Add found model names to the list found_models.extend(model_tags) # Record the genealogy for model_tag in model_tags: genealogy[model_tag].append(model) # Recursively check for more models for model_tag in model_tags: get_model_names(model_tag, genealogy, found_models) except Exception as e: print(f"Could not find model names for {model}: {e}") return found_models def find_root_nodes(G): """ Find all nodes in the graph with no predecessors """ return [n for n, d in G.in_degree() if d == 0] def max_width_of_tree(G): """ Calculate the maximum width of the tree """ max_width = 0 for root in find_root_nodes(G): width_at_depth = calculate_width_at_depth(G, root) local_max_width = max(width_at_depth.values()) max_width = max(max_width, local_max_width) return max_width def calculate_width_at_depth(G, root): """ Calculate width at each depth starting from a given root """ depth_count = defaultdict(int) queue = [(root, 0)] while queue: node, depth = queue.pop(0) depth_count[depth] += 1 for child in G.successors(node): queue.append((child, depth + 1)) return depth_count def create_family_tree(start_model): genealogy = defaultdict(list) get_model_names(start_model, genealogy) # Assuming this populates the genealogy # Create a directed graph G = nx.DiGraph() # Add nodes and edges to the graph for parent, children in genealogy.items(): for child in children: G.add_edge(parent, child) # Get max depth max_depth = nx.dag_longest_path_length(G) + 1 # Get max width max_width = max_width_of_tree(G) + 1 # Estimate plot size height = max(8, 1.6 * max_depth) width = max(8, 6 * max_width) # Set Graphviz layout attributes for a bottom-up tree plt.figure(figsize=(width, height)) pos = graphviz_layout(G, prog="dot") # Determine node colors based on license node_colors = [get_license_color(node) for node in G.nodes()] # Create a label mapping with line breaks labels = {node: node.replace("/", "\n") for node in G.nodes()} # Draw the graph nx.draw(G, pos, labels=labels, with_labels=True, node_color=node_colors, font_size=12, node_size=8_000, edge_color='black') # Create a legend for the colors legend_elements = [ Patch(facecolor='lightgreen', label='Permissive'), Patch(facecolor='lightcoral', label='Noncommercial'), Patch(facecolor='lightgray', label='Unknown') ] plt.legend(handles=legend_elements, loc='upper left') plt.title(f"{start_model}'s Family Tree", fontsize=20) # Capture the plot as an image in memory img_buffer = BytesIO() plt.savefig(img_buffer, format='png', bbox_inches='tight') plt.close() img_buffer.seek(0) # Open the image using PIL img = Image.open(img_buffer) return img with gr.Blocks() as demo: gr.Markdown(TITLE) model_id = gr.Textbox(label="Model ID", value="mlabonne/NeuralBeagle-7B") btn = gr.Button("Create tree") out = gr.Image() btn.click(fn=create_family_tree, inputs=model_id, outputs=out) demo.launch()