gguf

import numpy as np from gguf import GGUFWriter, GGUFReader, GGUFValueType # --- Writing a GGUF file --- output_file = "example.gguf" arch = "example_arch" writer = GGUFWriter(output_file, arch) writer.add_block_count(12) writer.add_uint32("answer", 42) writer.add_string("author", "AI Agent") # Add a tensor tensor_name = "my_example_tensor" tensor_data = np.ones((3, 4), dtype=np.float32) * 7.0 writer.add_tensor(tensor_name, tensor_data) # Finalize and write the file writer.write_header_to_file() writer.write_kv_to_file() writer.write_tensors_to_file() writer.close() print(f"Created GGUF file: {output_file}") # --- Reading a GGUF file --- reader = GGUFReader(output_file, 'r') reader.read_header() reader.read_kv() print(f"\nReading {output_file}:") print(f" GGUF Version: {reader.gguf_version}") print(" Metadata:") for key, value in reader.kv.items(): print(f" {key}: {value}") print(" Tensors (names and shapes):") for tensor in reader.tensors: print(f" - {tensor.name}: {tensor.shape}, {tensor.ggml_type.name}") # Example of loading a specific tensor (requires reading tensor data) # reader.read_tensors() # Uncomment this to load all tensor data into memory # if tensor_name in reader.tensors_by_name: # loaded_tensor = reader.tensors_by_name[tensor_name] # print(f" Loaded '{loaded_tensor.name}' data:\n{loaded_tensor.data}") reader.close()