🌳 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. See also mrfakename's version in this space.
""" 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/NeuralBeagle14-7B") btn = gr.Button("Create tree") out = gr.Image() btn.click(fn=create_family_tree, inputs=model_id, outputs=out) demo.queue(api_open=False).launch(show_api=False)