Parse string values for add_special_tokens in vLLM

[eldarkurtic]

When trying to evaluate reasoning models on e.g. AIME task, we would run evals like this:

MODEL=deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
MODEL_ARGS="pretrained=$MODEL,dtype=bfloat16,max_model_length=32768,gpu_memory_utilization=0.8,generation_parameters={max_new_tokens:32768,temperature:0.6,top_p:0.95}"
OUTPUT_DIR=data/evals/$MODEL

# AIME 2024
TASK=aime24
lighteval vllm $MODEL_ARGS "custom|$TASK|0|0" \
    --custom-tasks src/open_r1/evaluate.py \
    --use-chat-template \
    --output-dir $OUTPUT_DIR

As part of MODEL_ARGS we would like to be able to specify value for add_special_tokens to control whether BOS token is added or not by tokenizer. At the moment this is not possible because the given value will be interpreted as string whereas the codebase relies on boolean. This PR enables this by parsing add_special_tokens like other vLLM params are parsed in the class VLLMModel.