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554f767e08
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@ -227,8 +227,9 @@ class T5(torch.nn.Module):
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super().__init__()
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super().__init__()
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self.num_layers = config_dict["num_layers"]
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self.num_layers = config_dict["num_layers"]
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model_dim = config_dict["d_model"]
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model_dim = config_dict["d_model"]
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inner_dim = config_dict["d_kv"] * config_dict["num_heads"]
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self.encoder = T5Stack(self.num_layers, model_dim, model_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["is_gated_act"], config_dict["num_heads"], config_dict["model_type"] != "umt5", dtype, device, operations)
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self.encoder = T5Stack(self.num_layers, model_dim, inner_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["is_gated_act"], config_dict["num_heads"], config_dict["model_type"] != "umt5", dtype, device, operations)
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self.dtype = dtype
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self.dtype = dtype
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self.shared = operations.Embedding(config_dict["vocab_size"], model_dim, device=device, dtype=dtype)
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self.shared = operations.Embedding(config_dict["vocab_size"], model_dim, device=device, dtype=dtype)
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@ -36,9 +36,14 @@ a111:
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# models/diffusion_models
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# models/diffusion_models
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# models/unet
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# models/unet
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# embeddings: models/embeddings/
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# embeddings: models/embeddings/
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# gligen: models/gligen/
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# hypernetworks: models/hypernetworks/
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# loras: models/loras/
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# loras: models/loras/
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# photomaker: models/photomaker/
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# style_models: models/style_models/
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# upscale_models: models/upscale_models/
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# upscale_models: models/upscale_models/
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# vae: models/vae/
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# vae: models/vae/
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# vae_approx: models/vae_approx/
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#other_ui:
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#other_ui:
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# base_path: path/to/ui
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# base_path: path/to/ui
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