llama.cpp/gguf-py/examples/reader.py

48 lines
1.5 KiB
Python

#!/usr/bin/env python3
import logging
import sys
from pathlib import Path
from gguf.gguf_reader import GGUFReader
logger = logging.getLogger("reader")
sys.path.insert(0, str(Path(__file__).parent.parent))
def read_gguf_file(gguf_file_path):
"""
Reads and prints key-value pairs and tensor information from a GGUF file in an improved format.
Parameters:
- gguf_file_path: Path to the GGUF file.
"""
reader = GGUFReader(gguf_file_path)
# List all key-value pairs in a columnized format
logger.info("Key-Value Pairs:")
max_key_length = max(len(key) for key in reader.fields.keys())
for key, field in reader.fields.items():
value = field.parts[field.data[0]]
logger.info(f"{key:{max_key_length}} : {value}")
logger.info("----")
# List all tensors
logger.info("Tensors:")
tensor_info_format = "{:<30} | Shape: {:<15} | Size: {:<12} | Quantization: {}"
logger.info(tensor_info_format.format("Tensor Name", "Shape", "Size", "Quantization"))
logger.info("-" * 80)
for tensor in reader.tensors:
shape_str = "x".join(map(str, tensor.shape))
size_str = str(tensor.n_elements)
quantization_str = tensor.tensor_type.name
logger.info(tensor_info_format.format(tensor.name, shape_str, size_str, quantization_str))
if __name__ == '__main__':
if len(sys.argv) < 2:
logger.info("Usage: reader.py <path_to_gguf_file>")
sys.exit(1)
gguf_file_path = sys.argv[1]
read_gguf_file(gguf_file_path)