Update README.md

README.md

@@ -34,13 +34,14 @@ Only the weights of the linear operators within transformers blocks are quantize
 
 ### Use with vLLM
 
-This model can be deployed efficiently using the [vLLM](https://docs.vllm.ai/en/latest/) backend, as shown in the example below.
+This model can be deployed efficiently using the [vLLM](https://docs.vllm.ai/en/latest/) backend, as shown in the example below (using 2 GPUs).
 
 ```python
 from vllm import LLM, SamplingParams
 from transformers import AutoTokenizer
 
 model_id = "neuralmagic/Qwen2-72B-Instruct-quantized.w8a16"
+number_gpus = 2
 
 sampling_params = SamplingParams(temperature=0.7, top_p=0.8, max_tokens=256)
 
@@ -51,9 +52,9 @@ messages = [
     {"role": "user", "content": "Who are you?"},
 ]
 
-prompts = tokenizer.apply_chat_template(messages, tokenize=False)
+prompts = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
 
-llm = LLM(model=model_id)
+llm = LLM(model=model_id, tensor_parallel_size=number_gpus)
 
 outputs = llm.generate(prompts, sampling_params)
 
@@ -157,11 +158,11 @@ model.save_pretrained("Qwen2-72B-Instruct-quantized.w8a16")
 
 ## Evaluation
 
-The model was evaluated on the [OpenLLM](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) leaderboard tasks (version 1) with the [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness/tree/383bbd54bc621086e05aa1b030d8d4d5635b25e6) (commit 383bbd54bc621086e05aa1b030d8d4d5635b25e6) and the [vLLM](https://docs.vllm.ai/en/stable/) engine, using the following command:
+The model was evaluated on the [OpenLLM](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) leaderboard tasks (version 1) with the [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness/tree/383bbd54bc621086e05aa1b030d8d4d5635b25e6) (commit 383bbd54bc621086e05aa1b030d8d4d5635b25e6) and the [vLLM](https://docs.vllm.ai/en/stable/) engine, using the following command (using 8 GPUs):
 ```
 lm_eval \
   --model vllm \
-  --model_args pretrained="neuralmagic/Qwen2-72B-Instruct-quantized.w8a16",dtype=auto,gpu_memory_utilization=0.4,add_bos_token=True,max_model_len=4096 \
+  --model_args pretrained="neuralmagic/Qwen2-72B-Instruct-quantized.w8a16",dtype=auto,gpu_memory_utilization=0.4,add_bos_token=True,max_model_len=4096,tensor_parallel_size=8 \
   --tasks openllm \
   --batch_size auto
 ```