fix: default params

presets/inference/text-generation/inference_api.py

@@ -123,30 +123,18 @@ def health_check():
     return {"status": "Healthy"}
 
 class GenerateKwargs(BaseModel):
-    max_length: int = 200
+    max_length: int = 200 # Length of input prompt+max_new_tokens
     min_length: int = 0
-    do_sample: bool = True
+    do_sample: bool = False
     early_stopping: bool = False
     num_beams: int = 1
-    num_beam_groups: int = 1
-    diversity_penalty: float = 0.0
     temperature: float = 1.0
-    top_k: int = 10
+    top_k: int = 50
     top_p: float = 1
     typical_p: float = 1
     repetition_penalty: float = 1
-    length_penalty: float = 1
-    no_repeat_ngram_size: int = 0
-    encoder_no_repeat_ngram_size: int = 0
-    bad_words_ids: Optional[List[int]] = None
-    num_return_sequences: int = 1
-    output_scores: bool = False
-    return_dict_in_generate: bool = False
     pad_token_id: Optional[int] = tokenizer.pad_token_id
     eos_token_id: Optional[int] = tokenizer.eos_token_id
-    forced_bos_token_id: Optional[int] = None
-    forced_eos_token_id: Optional[int] = None
-    remove_invalid_values: Optional[bool] = None
     class Config:
         extra = Extra.allow # Allows for additional fields not explicitly defined
 
@@ -157,7 +145,7 @@ class UnifiedRequestModel(BaseModel):
     clean_up_tokenization_spaces: Optional[bool] = Field(False, description="Clean up extra spaces in text output")
     prefix: Optional[str] = Field(None, description="Prefix added to prompt")
     handle_long_generation: Optional[str] = Field(None, description="Strategy to handle long generation")
-    generate_kwargs: Optional[GenerateKwargs] = Field(None, description="Additional kwargs for generate method")
+    generate_kwargs: Optional[GenerateKwargs] = Field(default_factory=GenerateKwargs, description="Additional kwargs for generate method")
 
     # Field for conversational model
     messages: Optional[List[Dict[str, str]]] = Field(None, description="Messages for conversational model")