Delete awq_max.py

awq_max.py

@@ -1,48 +0,0 @@
-from awq import AutoAWQForCausalLM
-from transformers import AutoTokenizer
-
-# take in a model path and quantization args
-import argparse
-
-parser = argparse.ArgumentParser()
-parser.add_argument(
-    "--model_path", type=str, default="deepseek-ai/DeepSeek-R1-Distill-Qwen-14B"
-)
-parser.add_argument("--quant_path", type=str, default="r1-14b-awq-max-ptb")
-args = parser.parse_args()
-
-model_path = args.model_path
-quant_path = args.quant_path
-quant_config = {
-    "zero_point": True,
-    "q_group_size": 128,
-    "w_bit": 4,
-    "version": "GEMM",
-}
-
-
-# Load model
-model = AutoAWQForCausalLM.from_pretrained(model_path)
-tokenizer = AutoTokenizer.from_pretrained(
-    model_path,
-    trust_remote_code=True,
-)
-
-
-# Quantize
-model.quantize(
-    tokenizer,
-    quant_config=quant_config,
-    # calib_data="neuralmagic/LLM_compression_calibration",
-    # calib_data=get_long_dataset(),
-    # calib_data="ptb",
-    # max_calib_samples=128,
-    max_calib_seq_len=12288,
-    # n_parallel_calib_samples=128,
-)
-
-# Save quantized model
-model.save_quantized(quant_path)
-tokenizer.save_pretrained(quant_path)
-
-print(f'Model is quantized and saved at "{quant_path}"')