


"""simple docstring"""




from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCAmelCase			=							logging.get_logger(__name__)

__lowerCAmelCase			=							{
    "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json",
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}





class   __a      (   lowerCamelCase__				):
 __lowercase			:							int       					=			'biogpt'
 def __init__(       self    ,			lowerCAmelCase__=42_384    ,			lowerCAmelCase__=1_024    ,			lowerCAmelCase__=24    ,			lowerCAmelCase__=16    ,			lowerCAmelCase__=4_096    ,			lowerCAmelCase__="gelu"    ,			lowerCAmelCase__=0.1    ,			lowerCAmelCase__=0.1    ,			lowerCAmelCase__=1_024    ,			lowerCAmelCase__=0.0_2    ,			lowerCAmelCase__=1E-12    ,			lowerCAmelCase__=True    ,			lowerCAmelCase__=True    ,			lowerCAmelCase__=0.0    ,			lowerCAmelCase__=0.0    ,			lowerCAmelCase__=1    ,			lowerCAmelCase__=0    ,			lowerCAmelCase__=2    ,			**lowerCAmelCase__    ,			) ->    int:




        '''simple docstring'''
        lowercase__:       List[str]        =       vocab_size
        lowercase__:       List[Any]        =       max_position_embeddings
        lowercase__:       Tuple        =       hidden_size
        lowercase__:       int        =       num_hidden_layers
        lowercase__:       List[str]        =       num_attention_heads
        lowercase__:       int        =       intermediate_size
        lowercase__:       int        =       hidden_act
        lowercase__:       int        =       hidden_dropout_prob
        lowercase__:       str        =       attention_probs_dropout_prob
        lowercase__:       List[Any]        =       initializer_range
        lowercase__:       str        =       layer_norm_eps
        lowercase__:       Union[str, Any]        =       scale_embedding
        lowercase__:       Optional[Any]        =       use_cache
        lowercase__:       Union[str, Any]        =       layerdrop
        lowercase__:       Dict        =       activation_dropout
        super().__init__(pad_token_id=__A    ,			bos_token_id=__A    ,			eos_token_id=__A    ,			**__A			)






import torch

from diffusers import StableDiffusionPipeline


__lowerCAmelCase			=							'''path-to-your-trained-model'''
__lowerCAmelCase			=							StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('''cuda''')

__lowerCAmelCase			=							'''A photo of sks dog in a bucket'''
__lowerCAmelCase			=							pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save('''dog-bucket.png''')


