@@ -44,13 +44,13 @@ Please consult the documentation below to learn more about the parameters you ma
*`tokenizer_path`: Defaults to the `model_path`.
*`tokenizer_mode`: By default `auto`, see [here](https://huggingface.co/docs/transformers/en/main_classes/tokenizer) for different mode.
*`load_format`: The format the weights are loaded in. Defaults to `*.safetensors`/`*.bin`.
*`trust_remote_code`: If `True`, will use locally cached config files, otherwise use remote configs in HuggingFace.
*`trust_remote_code`: If `True`, will use locally cached config files, otherwise use remote configs in HuggingFace.
*`dtype`: Dtype used for the model, defaults to `bfloat16`.
*`kv_cache_dtype`: Dtype of the kv cache, defaults to the `dtype`.
*`context_length`: The number of tokens our model can process *including the input*. Not that extending the default might lead to strange behavior.
*`device`: The device we put the model, defaults to `cuda`.
*`chat_template`: The chat template to use. Deviating from the default might lead to unexpected responses. For multi-modal chat templates, refer to [here](https://docs.sglang.ai/backend/openai_api_vision.html#Chat-Template).
*`is_embedding`: Set to true to perform [embedding](https://docs.sglang.ai/backend/openai_api_embeddings.html) / [enocode](https://docs.sglang.ai/backend/native_api.html#Encode-(embedding-model)) and [reward](https://docs.sglang.ai/backend/native_api.html#Classify-(reward-model)) tasks.
*`is_embedding`: Set to true to perform [embedding](https://docs.sglang.ai/backend/openai_api_embeddings.html) / [encode](https://docs.sglang.ai/backend/native_api.html#Encode-(embedding-model)) and [reward](https://docs.sglang.ai/backend/native_api.html#Classify-(reward-model)) tasks.
*`revision`: Adjust if a specific version of the model should be used.
*`skip_tokenizer_init`: Set to true to provide the tokens to the engine and get the output tokens directly, typically used in RLHF.
*`json_model_override_args`: Override model config with the provided JSON.
