Merge branch 'Document-Custom-Model-Files' of https://github.com/Para…

…gEkbote/lighteval into Document-Custom-Model-Files

examples/model_configs/quantized_model.yaml

@@ -3,7 +3,7 @@ model:
     model_args: "pretrained=HuggingFaceH4/zephyr-7b-beta,revision=main" # pretrained=model_name,trust_remote_code=boolean,revision=revision_to_use,model_parallel=True.  To see the full list of parameters, please see here: https://huggingface.co/docs/lighteval/main/en/quicktour#model-arguments .
     dtype: "4bit"  # Specifying the model to be loaded in 4 bit uses BitsAndBytesConfig. The other option is to use "8bit" quantization.
     compile: true
-  merged_weights: # Ignore this section if you are not using PEFT models .
+  merged_weights: # Ignore this section if you are not using PEFT models.
     delta_weights: false # set to True of your model should be merged with a base model, also need to provide the base model name
     adapter_weights: false # set to True of your model has been trained with peft, also need to provide the base model name
     base_model: null # path to the base_model - needs to be specified only if delta_weights or adapter_weights is set to True 

examples/model_configs/serverless_model.yaml

@@ -1,3 +1,3 @@
 model:
   base_params:
-    model_name: "meta-llama/Llama-3.1-8B-Instruct" #Qwen/Qwen2.5-14B" #Qwen/Qwen2.5-7B".  #To see the full list of parameters, please see here: https://huggingface.co/docs/lighteval/package_reference/models#endpoints-based-models .
+    model_name: "meta-llama/Llama-3.1-8B-Instruct" #Qwen/Qwen2.5-14B" #Qwen/Qwen2.5-7B".  #To see the full list of parameters, please see here: https://huggingface.co/docs/lighteval/package_reference/models#endpoints-based-models