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Update README.md

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@@ -45,15 +45,22 @@ To run the inference on top of Llama 3.1 70B Instruct AWQ in INT4 precision, the
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  ```python
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  import torch
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- from transformers import AutoModelForCausalLM, AutoTokenizer
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  model_id = "hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4"
 
 
 
 
 
 
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  tokenizer = AutoTokenizer.from_pretrained(model_id)
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  model = AutoModelForCausalLM.from_pretrained(
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  model_id,
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  torch_dtype=torch.float16,
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  low_cpu_mem_usage=True,
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  device_map="auto",
 
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  )
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  prompt = [
 
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  ```python
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  import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer, AwqConfig
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  model_id = "hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4"
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+ quantization_config = AwqConfig(
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+ bits=4,
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+ fuse_max_seq_len=512, # Note: Update this as per your use-case
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+ do_fuse=True,
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+ )
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+
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  tokenizer = AutoTokenizer.from_pretrained(model_id)
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  model = AutoModelForCausalLM.from_pretrained(
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  model_id,
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  torch_dtype=torch.float16,
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  low_cpu_mem_usage=True,
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  device_map="auto",
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+ quantization_config=quantization_config
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  )
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  prompt = [