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Update README.md #291

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10 changes: 5 additions & 5 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -185,7 +185,7 @@ We use `lighteval` to evaluate models, with custom tasks defined in `src/open_r1

```shell
MODEL=deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,max_model_length=32768,gpu_memory_utilisation=0.8"
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,max_model_length=32768,gpu_memory_utilization=0.8"
OUTPUT_DIR=data/evals/$MODEL

# AIME 2024
Expand Down Expand Up @@ -218,7 +218,7 @@ To increase throughput across multiple GPUs, use _data parallel_ as follows:
```shell
NUM_GPUS=8
MODEL=deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,data_parallel_size=$NUM_GPUS,max_model_length=32768,gpu_memory_utilisation=0.8"
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,data_parallel_size=$NUM_GPUS,max_model_length=32768,gpu_memory_utilization=0.8"
TASK=aime24
OUTPUT_DIR=data/evals/$MODEL

Expand All @@ -233,7 +233,7 @@ For large models which require sharding across GPUs, use _tensor parallel_ and r
```shell
NUM_GPUS=8
MODEL=deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,tensor_parallel_size=$NUM_GPUS,max_model_length=32768,gpu_memory_utilisation=0.8"
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,tensor_parallel_size=$NUM_GPUS,max_model_length=32768,gpu_memory_utilization=0.8"
TASK=aime24
OUTPUT_DIR=data/evals/$MODEL

Expand Down Expand Up @@ -287,7 +287,7 @@ To reproduce these results use the following command:
```shell
NUM_GPUS=1 # Set to 8 for 32B and 70B models
MODEL=deepseek-ai/{model_name}
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,max_model_length=32768,gpu_memory_utilisation=0.8,tensor_parallel_size=$NUM_GPUS"
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,max_model_length=32768,gpu_memory_utilization=0.8,tensor_parallel_size=$NUM_GPUS"
OUTPUT_DIR=data/evals/$MODEL

lighteval vllm $MODEL_ARGS "custom|math_500|0|0" \
Expand Down Expand Up @@ -320,7 +320,7 @@ To reproduce these results use the following command:
```shell
NUM_GPUS=1 # Set to 8 for 32B and 70B models
MODEL=deepseek-ai/{model_name}
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,max_model_length=32768,gpu_memory_utilisation=0.8,tensor_parallel_size=$NUM_GPUS"
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,max_model_length=32768,gpu_memory_utilization=0.8,tensor_parallel_size=$NUM_GPUS"
OUTPUT_DIR=data/evals/$MODEL

lighteval vllm $MODEL_ARGS "custom|gpqa:diamond|0|0" \
Expand Down