DualMPNN takes the molecular graph as the input to pass through two encoders to get two node embeddings. A shared self-attention readout learns the node importance and produce two graph embedding vectors accordingly, which are then fed into two distinct fully connected layer to implement the pre...
embeddings = [] for i in range(0, video_224.shape[0], chunk_size): tmp = self.feature_extractor( images=video_224[i : i + chunk_size], do_normalize=True, do_center_crop=False, do_resize=False, do_rescale=False, return_tensors="pt", ).pixel_values.to(video.device, dtype=video...
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The image prompt adapter is designed to enable a pretrained text-to-image diffusion model to generate images with image prompt. - IP-Adapter/ip_adapter/ip_adapter_faceid.py at main · tencent-ailab/IP-Adapter
2024-09-03 20:06:48,714 - root - INFO - Adding extra search path embeddings F:\StabilityMatrix\Models\TextualInversion 2024-09-03 20:06:48,714 - root - INFO - Adding extra search path hypernetworks F:\StabilityMatrix\Models\Hypernetwork ...
python test/TrainStage1_inference.py --model_name_or_path "./checkpoints/vicuna-7b-v1-1" --LLaVA_model_path "./checkpoints/LLaVA-7B-v1" --save_dir './checkpoints/stage1_CC12M_alignment_7b/Results-100000' --pretrain_model "./checkpoints/stage1_CC12M_alignment_7b/embeddings_qformer...
def prepare_audio_embeddings(audio_waveform, audio_processor, audio_encoder, device, dtype): audio_waveform = audio_processor(audio_waveform, return_tensors="pt", sampling_rate=16000)['input_values'] audio_waveform = audio_waveform.to(device, dtype) audio_embeddings = audio_encoder(audio_wavefor...
parser.add_argument("--data_path", type=str, default='./data/data.h5ad', help='Path of data for generating the embeddings.') parser.add_argument("--model_path", type=str, default='./model.pth', help='Path of model training on the data.') parser.add_argument("--save_dir", typ...