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generation

Classes:

Name Description
StainedGlassGenerationConfig

A transformers.GenerationConfig with tokenizer aware settings, with empirically optimized settings for Stained Glass.

StainedGlassGenerationConfig

Bases: GenerationConfig

A transformers.GenerationConfig with tokenizer aware settings, with empirically optimized settings for Stained Glass.

Methods:

Name Description
__init__

Create a StainedGlassGenerationConfig.

from_tokenizer

Create a StainedGlassGenerationConfig using a tokenizer.

__init__

__init__(
    max_length: int,
    bos_token_id: int | None,
    pad_token_id: int | None,
    eos_token_id: int | None,
    temperature: float = 0.6,
    top_k: int = 5000,
    top_p: float = 0.9,
    repetition_penalty: float = 1.0,
    do_sample: Literal[True] = True,
    num_return_sequences: Literal[1] = 1,
    renormalize_logits: Literal[True] = True,
    **kwargs: Any,
) -> None

Create a StainedGlassGenerationConfig.

Parameters:

Name Type Description Default

max_length

int

The maximum number of tokens in the prompt and generated text combined.

required

bos_token_id

int | None

The token id for the beginning of the sequence.

required

pad_token_id

int | None

The token id for padding.

required

eos_token_id

int | None

The token id for the end of the sequence.

required

temperature

float

A setting controlling how conservative or creative the model responses are. Lower values such as 0.2 are terse, higher values such as above 1.0 are verbose and creative.

0.6

top_k

int

A positive integer representing the maximum number of tokens considered for sampling, ordered by likelihood.

5000

top_p

float

A positive real number in (0, 1.0) representing the amount of probabilistic mass which contributes to sampling tokens.

0.9

repetition_penalty

float

A penalty factor on generating repeated tokens.

1.0

do_sample

Literal[True]

Whether or not to use sampling ; use greedy decoding otherwise.

True

num_return_sequences

Literal[1]

The number of independently computed returned sequences for each element in the batch.

1

renormalize_logits

Literal[True]

Whether to renormalize the logits after applying all the logits processors or warper. It's highly recommended to set this flag to True as the search algorithms suppose the score logits are normalized.

True

**kwargs

Any

Additional keyword arguments to the generation config.

required

from_tokenizer classmethod

from_tokenizer(
    tokenizer: PreTrainedTokenizerBase,
    max_length: int,
    **kwargs: Any,
) -> StainedGlassGenerationConfig

Create a StainedGlassGenerationConfig using a tokenizer.

Parameters:

Name Type Description Default

tokenizer

PreTrainedTokenizerBase

The tokenizer whose pad, bos, and eos tokens are used for generation config.

required

max_length

int

The maximum number of tokens in the prompt and generated text combined.

required

**kwargs

Any

Additional keyword arguments to the generation config.

required

Returns:

Type Description
StainedGlassGenerationConfig

A Stained Glass generation config.