Update README.md
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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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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 = [
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