Upload New File

src/llmfactory/hparams/generating_args.py

+from dataclasses import asdict, dataclass, field
+from typing import Any, Dict, Optional
+
+
+@dataclass
+class GeneratingArguments:
+    r"""
+    Arguments pertaining to specify the decoding parameters.
+    """
+
+    do_sample: bool = field(
+        default=True,
+        metadata={"help": "Whether or not to use sampling, use greedy decoding otherwise."},
+    )
+    temperature: float = field(
+        default=0.95,
+        metadata={"help": "The value used to modulate the next token probabilities."},
+    )
+    top_p: float = field(
+        default=0.7,
+        metadata={
+            "help": "The smallest set of most probable tokens with probabilities that add up to top_p or higher are kept."
+        },
+    )
+    top_k: int = field(
+        default=50,
+        metadata={"help": "The number of highest probability vocabulary tokens to keep for top-k filtering."},
+    )
+    num_beams: int = field(
+        default=1,
+        metadata={"help": "Number of beams for beam search. 1 means no beam search."},
+    )
+    max_length: int = field(
+        default=1024,
+        metadata={"help": "The maximum length the generated tokens can have. It can be overridden by max_new_tokens."},
+    )
+    max_new_tokens: int = field(
+        default=1024,
+        metadata={"help": "The maximum numbers of tokens to generate, ignoring the number of tokens in the prompt."},
+    )
+    repetition_penalty: float = field(
+        default=1.0,
+        metadata={"help": "The parameter for repetition penalty. 1.0 means no penalty."},
+    )
+    length_penalty: float = field(
+        default=1.0,
+        metadata={"help": "Exponential penalty to the length that is used with beam-based generation."},
+    )
+    default_system: Optional[str] = field(
+        default=None,
+        metadata={"help": "Default system message to use in chat completion."},
+    )
+
+    def to_dict(self) -> Dict[str, Any]:
+        args = asdict(self)
+        if args.get("max_new_tokens", -1) > 0:
+            args.pop("max_length", None)
+        else:
+            args.pop("max_new_tokens", None)
+        return args