diff --git a/libs/langchain/langchain/llms/nlpcloud.py b/libs/langchain/langchain/llms/nlpcloud.py index 1420595eee9..d908e374e0f 100644 --- a/libs/langchain/langchain/llms/nlpcloud.py +++ b/libs/langchain/langchain/llms/nlpcloud.py @@ -28,8 +28,6 @@ class NLPCloud(LLM): """Language to use (multilingual addon)""" temperature: float = 0.7 """What sampling temperature to use.""" - min_length: int = 1 - """The minimum number of tokens to generate in the completion.""" max_length: int = 256 """The maximum number of tokens to generate in the completion.""" length_no_input: bool = True @@ -46,14 +44,8 @@ class NLPCloud(LLM): """The number of highest probability tokens to keep for top-k filtering.""" repetition_penalty: float = 1.0 """Penalizes repeated tokens. 1.0 means no penalty.""" - length_penalty: float = 1.0 - """Exponential penalty to the length.""" - do_sample: bool = True - """Whether to use sampling (True) or greedy decoding.""" num_beams: int = 1 """Number of beams for beam search.""" - early_stopping: bool = False - """Whether to stop beam search at num_beams sentences.""" num_return_sequences: int = 1 """How many completions to generate for each prompt.""" @@ -91,7 +83,6 @@ class NLPCloud(LLM): """Get the default parameters for calling NLPCloud API.""" return { "temperature": self.temperature, - "min_length": self.min_length, "max_length": self.max_length, "length_no_input": self.length_no_input, "remove_input": self.remove_input, @@ -100,10 +91,7 @@ class NLPCloud(LLM): "top_p": self.top_p, "top_k": self.top_k, "repetition_penalty": self.repetition_penalty, - "length_penalty": self.length_penalty, - "do_sample": self.do_sample, "num_beams": self.num_beams, - "early_stopping": self.early_stopping, "num_return_sequences": self.num_return_sequences, }