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LongCatImageTransformer2DModel
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You are viewing main version, which requires installation from source. If you'd like
regular pip install, checkout the latest stable version (v0.42.1).
LongCatImageTransformer2DModel
Model dapat dimuat dengan potongan kode berikut.
from diffusers import LongCatImageTransformer2DModel
transformer = LongCatImageTransformer2DModel.from_pretrained("meituan-longcat/LongCat-Image ", subfolder="transformer", dtype=torch.bfloat16)LongCatImageTransformer2DModel
kelas diffusers.LongCatImageTransformer2DModel
< source >( patch_size: int = 1in_channels: int = 64num_layers: int = 19num_single_layers: int = 38attention_head_dim: int = 128num_attention_heads: int = 24joint_attention_dim: int = 3584pooled_projection_dim: int = 3584axes_dims_rope: list = [16, 56, 56] )
Model Transformer yang diperkenalkan dalam Longcat-Image.
forward
< source >( hidden_states: Tensorencoder_hidden_states: Tensor = Nonetimestep: LongTensor = Noneimg_ids: Tensor = Nonetxt_ids: Tensor = Noneguidance: Tensor = Nonereturn_dict: bool = True )
Parameter
- hidden_states (
torch.FloatTensordengan bentuk(batch size, channel, height, width)) —hidden_statesmasukan. - encoder_hidden_states (
torch.FloatTensordengan bentuk(batch size, sequence_len, embed_dims)) — Embeddings kondisional (embeddings yang dihitung dari kondisi input seperti prompt) yang akan digunakan. - timestep (
torch.LongTensor) — Digunakan untuk menunjukkan langkah denoising. - img_ids (
torch.Tensor) — ID posisi gambar yang digunakan untuk menghitung embedding posisi rotasi. - txt_ids (
torch.Tensor) — ID posisi teks yang digunakan untuk menghitung embedding posisi rotasi. - guidance (
torch.Tensor, opsional) — Embedding skala panduan yang digunakan untuk varian model yang telah melalui distilasi panduan. - return_dict (
bool, opsional, defaultTrue) — Apakah akan mengembalikan~models.transformer_2d.Transformer2DModelOutputalih-alih tuple biasa.
Metode forward.