detector_benchmark.generation.generator¶
Classes¶
Module Contents¶
- class detector_benchmark.generation.generator.LLMGenerator(model: transformers.AutoModelForCausalLM, model_config: detector_benchmark.utils.configs.ModelConfig)¶
Bases:
torch.nn.Module- generator¶
- tokenizer¶
- device¶
- gen_params¶
- forward(samples: list, batch_size: int = 1, watermarking_scheme: detector_benchmark.watermark.auto_watermark.AutoWatermark | None = None) list[str]¶
Generate text from a list of input contexts.
Parameters:¶
- samples: list
A list of input contexts for text generation.
- batch_size: int
The batch size to use for generation. Defaults to 1.
- watermarking_scheme: AutoWatermark
The watermarking scheme to use for generation. If provided, it should be an instance of LogitsProcessor. Defaults to None.
Returns:¶
- list[str]
A list of generated texts.
- forward_debug(samples: list, batch_size: int = 1, watermarking_scheme: detector_benchmark.watermark.auto_watermark.AutoWatermark | None = None) list[str]¶
Takes a list of input contexts and generates text using the model.
Parameters:¶
- samples: list
A list of input contexts for text generation.
- batch_size: int
The batch size to use for generation.
- watermarking_scheme: LogitsProcessor
The watermarking scheme to use for generation.
Returns:¶
- tuple
A tuple containing the generated texts, the raw logits, and the processed logits.