Update README.md

README.md

@@ -13,9 +13,7 @@ library_name: transformers
 tags:
 - autoround
 - auto-round
-- autogptq
 - gptq
-- auto-gptq
 - woq
 - meta
 - pytorch
@@ -39,7 +37,9 @@ Quantized version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/m
 - 8 bits (INT8)
 - group size = 128
 - Asymmetrical Quantization
-- Method AutoGPTQ
+- Method WoQ (AutoRound format)
+  
+Fast and low memory, 2-3X speedup (slight accuracy drop at W4G128)
 
 Quantization framework: [Intel AutoRound](https://github.com/intel/auto-round)
 
@@ -75,8 +75,8 @@ pip install -vvv --no-build-isolation -e .[cpu]
   bits, group_size, sym, device, amp = 8, 128, False, 'cpu', False
   autoround = AutoRound(model, tokenizer, nsamples=128, iters=200, seqlen=512, batch_size=4, bits=bits, group_size=group_size, sym=sym, device=device, amp=amp)
   autoround.quantize()
-  output_dir = "./AutoRound/meta-llama_Llama-3.2-1B-Instruct-auto_gptq-int8-gs128-asym"
-  autoround.save_quantized(output_dir, format='auto_gptq', inplace=True)
+  output_dir = "./AutoRound/meta-llama_Llama-3.2-1B-Instruct-auto_round-int8-gs128-asym"
+  autoround.save_quantized(output_dir, format='auto_round', inplace=True)
 ```
 
 ## License