Update configs.py

configs.py

@@ -1,66 +1,400 @@
-T5_SHUNT_REPOS = {
+from __future__ import annotations
+from typing import Optional
+import logging
+logger = logging.getLogger(__name__)
+
+
+
+
+DEFAULT_REPOS = {
+    "clip_g": "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k",
+    "vit-bigG-14": "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k",
+    "clip_l": "openai/clip-vit-large-patch14",
+    "vit-l-14": "openai/clip-vit-large-patch14",
+    "clip_l_4h": "openai/clip-vit-large-patch14",
+    "clip_l_x52": "AbstractPhil/beatrix-x52",
+    "clip_h": "openai/clip-vit-large-patch14-h",
+    "clip_vision": "openai/clip-vit-large-patch14-vision",
+    "t5_base": "google/flan-t5-base",
+    "t5_small": "google-t5/t5-small",
+    "t5_unchained": "AbstractPhil/t5-unchained",
+    "bert_beatrix": "AbstractPhil/bert-beatrix-2048",
+    "nomic_bert": "nomic-ai/nomic-bert-2048",
+    "mobilebert": "google/mobilebert-uncased",
+    "bert_base_uncased": "bert-base-uncased",
+    "bert_large_uncased": "bert-large-uncased",
+    "bert_base_cased": "bert-base-cased",
+    "bert_base_multilingual": "bert-base-multilingual-uncased",
+    "bert_base_multilingual_cased": "bert-base-multilingual-cased",
+}
+
+HARMONIC_SHUNT_REPOS = {
     "clip_g": {
-        "models": ["vit-bigG-14", 'flan-t5-base'],
+        "models": ['t5_base', "clip_g"],
+        "repo": "AbstractPhil/t5-flan-base-vit-bigG-14-dual-stream-adapter",
+        "shunts_available": {
+            "shunt_type_name": "DualStreamAdapter-G",
+            "config_file_name": "config.json",
+            "shunt_list": [
+                {"name": "flan-t5-base+clip_g:caption", "file": "t5-flan-vit-bigG-14-dual_shunt_caption.safetensors" },
+                {"name": "flan-t5-base+clip_g:noise-e1", "file": "t5-flan-vit-bigG-14-dual_shunt_no_caption_e1.safetensors" },
+                {"name": "flan-t5-base+clip_g:noise-e3", "file": "t5-flan-vit-bigG-14-dual_shunt_no_caption_e2.safetensors" },
+                {"name": "flan-t5-base+clip_g:noise-e3", "file": "t5-flan-vit-bigG-14-dual_shunt_no_caption_e3.safetensors" },
+                {"name": "flan-t5-base+clip_g:summarize", "file": "t5-flan-vit-bigG-14-dual_shunt_summarize.safetensors" },
+                {"name": "flan-t5-base+clip_g_omega32:noise-10000", "file": "dual_shunt_omega_no_caption_e1_step_10000.safetensors" },
+                {"name": "flan-t5-base+clip_g_omega32:noise-1000", "file": "dual_shunt_omega_no_caption_noised_e1_step_1000.safetensors" },
+                {"name": "flan-t5-base+clip_g_omega32:noise-4000", "file": "dual_shunt_omega_no_caption_noised_e1_step_4000.safetensors" },
+                {"name": "flan-t5-base+clip_g_omega32:noise-10000v2", "file": "dual_shunt_omega_no_caption_noised_e1_step_10000.safetensors" },
+            ],
+        },
         "config": {
             "adapter_id": "003", "name": "DualShuntAdapter-G",
-            "t5": {
+            "condition_encoders": [{
+                "type": "t5_base",
                 "model": "google/flan-t5-base",
                 "hidden_size": 768
-            },
-            "clip": {
-                "model": "openai/clip-vit-large-patch14",
-                "hidden_size": 1280
-            },
+            }],
+            "modulation_encoders": [
+                {
+                    "type": "clip_g",
+                    "model": "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k",
+                    "hidden_size": 1280
+                }
+            ],
             "hidden_size": 1280,  # This is the adapter's output size
             "bottleneck": 640, "heads": 20,
-            "tau_init": 0.1, "max_guidance": 10.0,
-            "proj_layers": 2, "layer_norm": True, "dropout": 0.1,
-            "use_dropout": True, "use_proj_stack": True, "assert_input_dims": True,
+            "max_guidance": 10.0, "tau_init": 0.1,
+            "proj_layers": 2, "layer_norm": True, "dropout": 0.0,
+            "use_dropout": False, "use_proj_stack": True, "assert_input_dims": True,
             "routing": {"type": "cross_attention", "enable_causal_mask": False, "bidirectional": True},
             "version": "v0.3.2"
         },
-        "repo": "AbstractPhil/t5-flan-base-vit-bigG-14-dual-stream-adapter",
+    },
+    "clip_g_8h": {
+        "models": ['bert_beatrix-2048', "clip_g"],
+        "repo": "AbstractPhil/bert-beatrix-2048-vit-bigG-14-dual-shunt-adapter",
         "shunts_available": {
             "shunt_type_name": "DualStreamAdapter-G",
             "config_file_name": "config.json",
             "shunt_list": [
-                "t5-flan-vit-bigG-14-dual_shunt_caption.safetensors",
-                "t5-flan-vit-bigG-14-dual_shunt_no_caption_e1.safetensors",
-                "t5-flan-vit-bigG-14-dual_shunt_no_caption_e2.safetensors",
-                "t5-flan-vit-bigG-14-dual_shunt_no_caption_e3.safetensors",
-                "t5-flan-vit-bigG-14-dual_shunt_summarize.safetensors",
-                "dual_shunt_omega_no_caption_e1_step_10000.safetensors",
-                "dual_shunt_omega_no_caption_noised_e1_step_1000.safetensors",
-                "dual_shunt_omega_no_caption_noised_e1_step_4000.safetensors",
-                "dual_shunt_omega_no_caption_noised_e1_step_10000.safetensors",
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e1", "file": "dual_shunt_g_laion_no_caption_e1.safetensors"},
+                {"name": "beatrix+clip_g-booru_v1_8h:noise-3000", "file": "dual_shunt_g_booru_no_caption_noised_e1_step_3000.safetensors"},
+                {"name": "beatrix+clip_g-booru_v1_8h:noise-5000", "file": "dual_shunt_g_booru_no_caption_noised_e1_step_5000.safetensors"},
+                {"name": "beatrix+clip_g-booru_v1_8h:noise-7000", "file": "dual_shunt_g_booru_no_caption_noised_e1_step_7000.safetensors"},
+                {"name": "beatrix+clip_g-booru_v1_8h:noise-10000", "file": "dual_shunt_g_booru_no_caption_noised_e1_step_10000.safetensors"},
+                {"name": "beatrix+clip_g-booru_v1_8h:noise-14000", "file": "dual_shunt_g_booru_no_caption_noised_e1_step_14000.safetensors"},
+                {"name": "beatrix+clip_g-booru_v1_8h:noise-20000", "file": "dual_shunt_g_booru_no_caption_noised_e1_step_20000.safetensors"},
+                {"name": "beatrix+clip_g-booru_v1_8h:noise-25000", "file": "dual_shunt_g_booru_no_caption_noised_e1_step_25000.safetensors"},
+                {"name": "beatrix+clip_g-booru_v1_8h:noise-30000", "file": "dual_shunt_g_booru_no_caption_noised_e1_step_30000.safetensors"},
+                {"name": "beatrix+clip_g-booru_v1_8h:noise-e1", "file": "dual_shunt_g_booru_no_caption_noised_e1_final.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e2", "file": "dual_shunt_g_laion_no_caption_e2.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e5", "file": "dual_shunt_g_laion_no_caption_e5.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e8", "file": "dual_shunt_g_laion_no_caption_e8.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e10", "file": "dual_shunt_g_laion_no_caption_e10.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e12", "file": "dual_shunt_g_laion_no_caption_e12.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e15", "file": "dual_shunt_g_laion_no_caption_e15.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e16", "file": "dual_shunt_g_laion_no_caption_e16.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e17", "file": "dual_shunt_g_laion_no_caption_e17.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e18", "file": "dual_shunt_g_laion_no_caption_e18.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e19", "file": "dual_shunt_g_laion_no_caption_e19.safetensors"},
+                {"name": "beatrix+clip_g-laion_v1_8h:noise-e20", "file": "dual_shunt_g_laion_no_caption_e20.safetensors"},
             ],
-        }
+        },
+        "config": {
+            "adapter_id": "006", "name": "DualShuntAdapter-G",
+            "condition_encoders": [{
+                "type": "t5_base",
+                "model": "AbstractPhil/bert-beatrix-2048",
+                "hidden_size": 768
+            }],
+            "modulation_encoders": [
+                {
+                    "type": "clip_g",
+                    "model": "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k",
+                    "hidden_size": 1280
+                }
+            ],
+            "hidden_size": 1280,  # This is the adapter's output size
+            "bottleneck": 640, "heads": 8,
+            "max_guidance": 10.0, "tau_init": 0.1,
+            "proj_layers": 2, "layer_norm": True, "dropout": 0.0,
+            "use_dropout": False, "use_proj_stack": True, "assert_input_dims": True,
+            "routing": {"type": "cross_attention", "enable_causal_mask": False, "bidirectional": True},
+            "version": "v0.3.2"
+        },
     },
-    "clip_l": {
+#
+    "clip_l_4h_bert": {
+        "models": ["bert-beatrix-2048", "clip_l"],
+        "repo": "AbstractPhil/bert-beatrix-2048-vit-l-14-dual-shunt-adapter",
+        "shunts_available": {
+            "shunt_type_name": "DualStreamAdapter-L",
+            "config_file_name": "config.json",
+            "shunt_list": [
+                {"name": "beatrix+clip_l-4h:noise_5000", "file": "dual_shunt_l_booru_no_caption_noised_e1_step_5000.safetensors"},
+                {"name": "beatrix+clip_l-4h:noise_10000", "file": "dual_shunt_l_booru_no_caption_noised_e1_step_10000.safetensors"},
+                {"name": "beatrix+clip_l-4h:noise_15000", "file": "dual_shunt_l_booru_no_caption_noised_e1_step_15000.safetensors"},
+                {"name": "beatrix+clip_l-4h:noise_20000", "file": "dual_shunt_l_booru_no_caption_noised_e1_step_20000.safetensors"},
+                {"name": "beatrix+clip_l-4h:noise_25000", "file": "dual_shunt_l_booru_no_caption_noised_e1_step_25000.safetensors"},
+            ],
+        },
+        "config": {
+            "adapter_id": "005",
+            "name": "DualShuntAdapter",
+            "condition_encoders": [{
+                "type": "bert_beatrix",
+                "model": "AbstractPhil/bert-beatrix-2048",
+                "hidden_size": 768
+            }],
+            "modulation_encoders": [{
+                "type": "clip_l",
+                "model": "openai/clip-vit-large-patch14",
+                "hidden_size": 768
+            }],
+            "hidden_size": 768,  # This is the adapter's output size
+            "bottleneck": 384, "heads": 4,
+            "max_guidance": 10.0, "tau_init": 0.1,
+            "proj_layers": 2, "layer_norm": True, "dropout": 0.0,
+            "use_dropout": False, "use_proj_stack": True, "assert_input_dims": True,
+            "routing": {"type": "cross_attention", "enable_causal_mask": False, "bidirectional": True},
+            "version": "v0.3.2"
+        },
+    },
+    "clip_l_4h": {
         "models": ["vit-l-14", 'flan-t5-base'],
+        "repo": "AbstractPhil/t5-flan-base-vit-l-14-dual-stream-adapter",
+        "shunts_available": {
+            "shunt_type_name": "DualStreamAdapter-L",
+            "config_file_name": "config.json",
+            "shunt_list": [
+                {"name": "t5+clip_l_4h:noise_13m", "file": "t5-vit-l-14-dual_shunt_booru_13_000_000.safetensors"},
+                {"name": "t5+clip_l_4h:noise_51.2m", "file": "t5-vit-l-14-dual_shunt_booru_51_200_000.safetensors"}
+            ],
+        },
+        "config": {
+            "adapter_id": "003",
+            "name": "DualShuntAdapter",
+            "condition_encoders": [{
+                "type": "t5_base",
+                "model": "google/flan-t5-base",
+                "hidden_size": 768
+            }],
+            "modulation_encoders": [{
+                "type": "clip_l",
+                "model": "openai/clip-vit-large-patch14",
+                "hidden_size": 768
+            }],
+            "hidden_size": 768,  # This is the adapter's output size
+            "bottleneck": 384, "heads": 4,
+            "max_guidance": 10.0, "tau_init": 0.1,
+            "proj_layers": 2, "layer_norm": True, "dropout": 0.0,
+            "use_dropout": False, "use_proj_stack": True, "assert_input_dims": True,
+            "routing": {"type": "cross_attention", "enable_causal_mask": False, "bidirectional": True},
+            "version": "v0.3.2"
+        },
+    },
+    "clip_l_x52": {
+        "models": ['bert-beatrix-2048', 'vit-l-14'],
+        "repo": "AbstractPhil/beatrix-x52",
+        "shunts_available": {
+            "shunt_type_name": "HarmonicBank-x52",
+            "config_file_name": "config.json",
+            "shunt_list": [
+                {"name": "beatrix-x52", "file": "AbstractPhil/beatrix-x52-v0001.safetensors"},
+            ]
+        },
+        "config": {
+            "adapter_id": "072",
+            "name": "DualShuntAdapter",
+            "condition_encoders": [
+                {
+                    "model": "AbstractPhil/bert-beatrix-2048"
+                },
+            ],
+            "modulation_encoders": [
+                {
+                    "model": "openai/clip-vit-large-patch14",
+                    "offset_slip": 0.0,
+                    "slip_frequency": 0.27
+                },
+                {
+                    "model": "AbstractPhil/clips/Omega-SIM-ViT-CLIP_L_FP32.safetensors",
+                    "offset_slip": 1.0,
+                    "slip_frequency": 0.27
+                },
+                {
+                    "model": "AbstractPhil/clips/ComfyUI_noobxl-R9_clip_l.safetensors",
+                    "offset_slip": 2.0,
+                    "slip_frequency": 0.27
+                },
+                {
+                    "model": "AbstractPhil/clips/SIM-VPRED-Ω-73-clip_l.safetensors",
+                    "offset_slip": 3.0,
+                    "slip_frequency": 0.27
+                },
+            ],
+            "hidden_size": 768,  # This is the adapter's output size
+            "resonant_heads": 2000, # number of resonant heads to distribute across the shunts
+            "spin": 0.5,  # the spin factor that this shunt was trained on
+            "conv_frequency": 0.29152, # the differentiation frequency of each rope layered phase
+            "conv_layers": 52000, # number of convolutional layers
+            "use_bottleneck": False,  # bottleneck can be enabled for a much more expensive overhead
+            "bottleneck": 32,  # This is the bottleneck dim size per shunt if used
+            "heads": 2, # number of heads per shunt if bottleneck enabled eg 104,000 heads total which is a shitload
+            "max_guidance": 10.0,
+            "tau_init": 0.1,
+            "proj_layers": 16,
+            "layer_norm": True,
+            "dropout": 0.0,
+            "use_dropout": False,
+            "use_proj_stack": True,
+            "assert_input_dims": True,
+            "routing": {
+                "type": "phase_gate",
+                "math": "tau",
+                "rope_phase_offset": 0.0,
+                "omnidirectional": False,
+                "loosely_coupled": True,
+            },
+            "version": "v2.0.0",
+
+        },
+    },
+    "clip_l": {
+        "models": ['flan-t5-base', "vit-l-14"],
+        "repo": "AbstractPhil/t5-flan-base-vit-l-14-dual-stream-adapter",
         "config": {
             "adapter_id": "002",
             "name": "DualShuntAdapter",
-            "t5": {"model": "google/flan-t5-base", "hidden_size": 768},
-            "clip": {"model": "openai/clip-vit-large-patch14", "hidden_size": 768},
+            "condition_encoders": [{
+                "type": "t5_base",
+                "model": "google/flan-t5-base",
+                "hidden_size": 768
+            }],
+            "modulation_encoders": [{
+                "type": "clip_l",
+                "model": "openai/clip-vit-large-patch14",
+                "hidden_size": 768
+            }],
             "hidden_size": 768,  # This is the adapter's output size
             "bottleneck": 384, "heads": 12,
-            "tau_init": 0.1, "max_guidance": 10.0,
-            "proj_layers": 2, "layer_norm": True, "dropout": 0.1,
-            "use_dropout": True, "use_proj_stack": True, "assert_input_dims": True,
+            "max_guidance": 10.0, "tau_init": 0.1,
+            "proj_layers": 2, "layer_norm": True, "dropout": 0.0,
+            "use_dropout": False, "use_proj_stack": True, "assert_input_dims": True,
+            "routing": {"type": "cross_attention", "enable_causal_mask": False, "bidirectional": True},
+            "version": "v0.3.2"
+        },
+        "shunts_available": {
+            "shunt_type_name": "DualStreamAdapter-L",
+            "config_file_name": "config.json",
+            "shunt_list": [
+                {"name": "t5+clip_l_12h:caption-20m", "file": "t5-vit-l-14-dual_shunt_caption.safetensors" },
+                {"name": "t5+clip_l_12h:noise-20m", "file": "t5-vit-l-14-dual_shunt_no_caption.safetensors" },
+                {"name": "t5+clip_l_12h:summarize-20m", "file": "t5-vit-l-14-dual_shunt_summarize.safetensors" },
+            ],
+        },
+    },
+    #AbstractPhil/bert-beatrix-2048-noobxl-epsilon-v11-dual-shunt-adapter_clip_g
+    "clip_g_noob": {
+        "models": ['bert-beatrix-2048', "clip_g"],
+        "repo": "AbstractPhil/bert-beatrix-2048-noobxl-epsilon-v11-dual-shunt-adapter_clip_g",
+        "config": {
+            "adapter_id": "006",
+            "name": "DualShuntAdapter",
+            "condition_encoders": [{
+                "type": "bert_beatrix",
+                "model": "AbstractPhil/bert-beatrix-2048",
+                "hidden_size": 768
+            }],
+            "modulation_encoders": [{
+                "type": "clip_g",
+                "model": "AbstractPhil/clips/NAI-11-epsilon_clip_g.safetensors",
+                "hidden_size": 1280
+            }],
+            "hidden_size": 1280,  # This is the adapter's output size
+            "bottleneck": 640, "heads": 8,
+            "max_guidance": 10.0, "tau_init": 0.1,
+            "proj_layers": 2, "layer_norm": True, "dropout": 0.0,
+            "use_dropout": False, "use_proj_stack": True, "assert_input_dims": True,
+            "routing": {"type": "cross_attention", "enable_causal_mask": False, "bidirectional": True},
+            "version": "v0.3.2"
+        },
+        "shunts_available": {
+            "shunt_type_name": "DualStreamAdapter-G",
+            "config_file_name": "config.json",
+            "shunt_list": [
+                {"name": "beatrix+noob_g_8h:noised-1000", "file": "dual_shunt_g_noob_no_caption_e1_step_1000.safetensors"},
+                {"name": "beatrix+noob_g_8h:noised-2000", "file": "dual_shunt_g_noob_no_caption_e1_step_2000.safetensors"},
+                {"name": "beatrix+noob_g_8h:noised-3000", "file": "dual_shunt_g_noob_no_caption_e1_step_3000.safetensors"},
+                {"name": "beatrix+noob_g_8h:noised-4000", "file": "dual_shunt_g_noob_no_caption_e1_step_4000.safetensors"},
+                {"name": "beatrix+noob_g_8h:noised-5000", "file": "dual_shunt_g_noob_no_caption_e1_step_5000.safetensors"},
+                {"name": "beatrix+noob_g_8h:noised-6000", "file": "dual_shunt_g_noob_no_caption_e1_step_6000.safetensors"},
+                {"name": "beatrix+noob_g_8h:noised-7000", "file": "dual_shunt_g_noob_no_caption_e1_step_7000.safetensors"},
+                {"name": "beatrix+noob_g_8h:noised-8000", "file": "dual_shunt_g_noob_no_caption_e1_step_8000.safetensors"},
+            ]
+        },
+    },
+
+
+    "clip_l_noob": {
+        "models": ['bert-beatrix-2048', "vit-l-14"],
+        "repo": "AbstractPhil/bert-beatrix-2048-noobxl-epsilon-v11-dual-shunt-adapter",
+        "config": {
+            "adapter_id": "002",
+            "name": "DualShuntAdapter",
+            "condition_encoders": [{
+                "type": "bert_beatrix",
+                "model": "AbstractPhil/bert-beatrix-2048",
+                "hidden_size": 768
+            }],
+            "modulation_encoders": [{
+                "type": "clip_l",
+                "model": "AbstractPhil/clips/NAI-11-epsilon_clip_l.safetensors",
+                "hidden_size": 768
+            }],
+            "hidden_size": 768,  # This is the adapter's output size
+            "bottleneck": 384, "heads": 4,
+            "max_guidance": 10.0, "tau_init": 0.1,
+            "proj_layers": 2, "layer_norm": True, "dropout": 0.0,
+            "use_dropout": False, "use_proj_stack": True, "assert_input_dims": True,
             "routing": {"type": "cross_attention", "enable_causal_mask": False, "bidirectional": True},
             "version": "v0.3.2"
         },
-        "repo": "AbstractPhil/t5-flan-base-vit-l-14-dual-stream-adapter",
         "shunts_available": {
             "shunt_type_name": "DualStreamAdapter-L",
             "config_file_name": "config.json",
             "shunt_list": [
-                "t5-vit-l-14-dual_shunt_caption.safetensors",
-                "t5-vit-l-14-dual_shunt_no_caption.safetensors",
-                "t5-vit-l-14-dual_shunt_summarize.safetensors",
-                "t5-vit-l-14-dual_shunt_booru_13_000_000.safetensors",
-                "t5-vit-l-14-dual_shunt_booru_51_200_000.safetensors",
+                {"name": "beatrix+noob_l_4h:noise-5000", "file": "beatrix_dual_shunt_l_noob_e1_step_5000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-10000", "file": "beatrix_dual_shunt_l_noob_e1_step_10000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-15000", "file": "beatrix_dual_shunt_l_noob_e1_step_15000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-20000", "file": "beatrix_dual_shunt_l_noob_e1_step_20000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-25000", "file": "beatrix_dual_shunt_l_noob_e1_step_25000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-30000", "file": "beatrix_dual_shunt_l_noob_e1_step_30000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-35000", "file": "beatrix_dual_shunt_l_noob_e1_step_35000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-40000", "file": "beatrix_dual_shunt_l_noob_e1_step_40000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-45000", "file": "beatrix_dual_shunt_l_noob_e1_step_45000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-50000", "file": "beatrix_dual_shunt_l_noob_e1_step_50000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-55000", "file": "beatrix_dual_shunt_l_noob_e1_step_55000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-60000", "file": "beatrix_dual_shunt_l_noob_e1_step_60000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-65000", "file": "beatrix_dual_shunt_l_noob_e1_step_65000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-70000", "file": "beatrix_dual_shunt_l_noob_e1_step_70000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-75000", "file": "beatrix_dual_shunt_l_noob_e1_step_75000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-80000", "file": "beatrix_dual_shunt_l_noob_e1_step_80000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-85000", "file": "beatrix_dual_shunt_l_noob_e1_step_85000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-90000", "file": "beatrix_dual_shunt_l_noob_e1_step_90000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-100000", "file": "beatrix_dual_shunt_l_noob_e1_step_100000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-120000", "file": "beatrix_dual_shunt_l_noob_e1_step_120000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-140000", "file": "beatrix_dual_shunt_l_noob_e1_step_140000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-150000", "file": "beatrix_dual_shunt_l_noob_e1_step_150000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-160000", "file": "beatrix_dual_shunt_l_noob_e1_step_160000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-180000", "file": "beatrix_dual_shunt_l_noob_e1_step_180000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-200000", "file": "beatrix_dual_shunt_l_noob_e1_step_200000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-225000", "file": "beatrix_dual_shunt_l_noob_e1_step_225000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-250000", "file": "beatrix_dual_shunt_l_noob_e1_step_250000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-275000", "file": "beatrix_dual_shunt_l_noob_e1_step_275000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-300000", "file": "beatrix_dual_shunt_l_noob_e1_step_300000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-310000", "file": "beatrix_dual_shunt_l_noob_e1_step_310000.safetensors"},
+                {"name": "beatrix+noob_l_4h:noise-314000", "file": "beatrix_dual_shunt_l_noob_e1_step_314000.safetensors"},
             ],
         },
     }
@@ -68,38 +402,173 @@ T5_SHUNT_REPOS = {
 
 # ─── Adapter Configs ─────────────────────────────────────────────
 
-BERT_CONFIGS = {
+ENCODER_CONFIGS = {
+    "bert-beatrix-2048": {
+        "repo_name": "AbstractPhil/bert-beatrix-2048",
+        "name": "bert-beatrix-2048",
+        "type": "nomic_bert",
+        "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+        "use_remote_code": True,
+        "subfolder": "",
+    },
+    "nomic-bert-2048": {
+        "repo_name": "nomic-ai/nomic-bert-2048",
+        "name": "nomic-bert-2048",
+        "type": "nomic_bert",
+        "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+        "use_remote_code": True,
+        "subfolder": "",
+    },
     "mobilebert-base-uncased": {
         "repo_name": "google/mobilebert-uncased",
+        "name": "mobilebert-base-uncased",
+        "type": "mobilebert",
         "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
         "subfolder": "",
     },
     "bert-base-uncased": {
         "repo_name": "bert-base-uncased",
+        "name": "bert-base-uncased",
+        "type": "bert",
         "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
     },
     "bert-large-uncased": {
         "repo_name": "bert-large-uncased",
+        "name": "bert-large-uncased",
+        "type": "bert",
         "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
     },
     "bert-base-cased": {
         "repo_name": "bert-base-cased",
+        "name": "bert-base-cased",
+        "type": "bert",
         "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
-    }
-}
+    },
+    "bert-large-cased": {
+        "repo_name": "google-bert/bert-large-cased",
+        "name": "bert-large-cased",
+        "type": "bert",
+        "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+    },
+    "bert-base-multilingual-cased": {
+        "repo_name": "google-bert/bert-base-multilingual-cased",
+        "name": "bert-base-multilingual-cased",
+        "type": "bert",
+        "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+    },
+    "t5xxl": {
+        "repo_name": "google/t5-xxl-lm-adapt",
+        "name": "t5-xxl",
+        "type": "t5",
+        "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+        "subfolder": "",
+    },
+    "distill-t5-base-4096": {
+        "repo_name": "LifuWang/DistillT5",
+        "name": "distill-t5-base-4096",
+        "type": "t5_encoder_with_projection",
+        "tokenizer": "t5_override", # only required if the tokenizer is missing from the model repo
+        "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+        "subfolder": "",
+    },
+    "distill-t5-small-4096": {
+        "repo_name": "LifuWang/DistillT5-Small",
+        "name": "distill-t5-small-4096",
+        "type": "t5_encoder_with_projection",
+        "tokenizer": "t5_override", # only required if the tokenizer is missing from the model repo
+        "use_huggingface": True,
+        # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+        "subfolder": "",
+    },
+    "distill-t5-large-4096": {
+        "repo_name": "LifuWang/DistillT5-Large",
+        "name": "distill-t5-large-4096",
+        "type": "t5_encoder_with_projection",
+        "tokenizer": "t5_override", # only required if the tokenizer is missing from the model repo
+        "use_huggingface": True,
+        # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+        "subfolder": "",
+    },
 
-T5_CONFIGS = {
+    "t5xxl-unchained": {
+        "repo_name": "AbstractPhil/t5xxl-unchained",
+        "name": "t5xxl-unchained-f16",
+        "type": "t5",
+        "use_huggingface": True,  # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+        "subfolder": "",
+        #"tokenizer": "t5-unchained",
+        "file_name": "t5xxl-unchained-f16.safetensors",
+        "config": {
+            "config_file_name": "config.json",
+            "architectures": [
+                "T5ForConditionalGeneration"
+            ],
+            "attention_dropout": 0.0,
+            "classifier_dropout": 0.0,
+
+            "d_ff": 10240,
+            "d_kv": 64,
+            "d_model": 4096,
+            "decoder_start_token_id": 0,
+            "dropout_rate": 0.0,
+            "eos_token_id": 1,
+            "dense_act_fn": "gelu_pytorch_tanh",
+            "initializer_factor": 1.0,
+            "is_encoder_decoder": True,
+            "is_gated_act": True,
+            "layer_norm_epsilon": 1e-06,
+            "model_type": "t5",
+            "num_decoder_layers": 24,
+            "num_heads": 64,
+            "num_layers": 24,
+            "output_past": True,
+            "pad_token_id": 0,
+            "relative_attention_num_buckets": 32,
+            "tie_word_embeddings": False,
+            "vocab_size": 69328,
+        }
+    },
+    "flan-t5-small": {
+        "repo_name": "google/flan-t5-small",
+        "name": "flan-t5-small",
+        "type": "t5",
+        "use_huggingface": True,
+        # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+    },
     "flan-t5-base": {
         "repo_name": "google/flan-t5-base",
+        "name": "flan-t5-base",
+        "type": "t5",
+        "use_huggingface": True, # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+    },
+    "flan-t5-large": {
+        "repo_name": "google/flan-t5-large",
+        "name": "flan-t5-large",
+        "type": "t5",
+        "use_huggingface": True, # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+    },
+    "flan-t5-xl": {
+        "repo_name": "google/flan-t5-xl",
+        "name": "flan-t5-xl",
+        "type": "t5",
+        "use_huggingface": True, # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
+    },
+    "flan-t5-xxl": {
+        "repo_name": "google/flan-t5-xxl",
+        "name": "flan-t5-xxl",
+        "type": "t5",
         "use_huggingface": True, # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
     },
     "t5-small": {
         "repo_name": "google-t5/t5-small",
+        "name": "t5-small",
+        "type": "t5",
         "use_huggingface": True, # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
-
     },
     "t5_small_human_attentive_try2_pass3": {
-        "repo_name": "AbstractPhil/t5_small_human_attentive_try2_pass3",
+        "repo_name": "AbstractPhil/T5-Small-Human-Attentive-Try2-Pass3",
+        "name": "t5_small_human_attentive_try2_pass3",
+        "type": "t5",
         "use_huggingface": True, # defaults to simple loading from HuggingFace, if False, will use repo_name and subfolder
         # the necessary config is present here for posterity in case it fails to load from HuggingFace.
         "subfolder": "",
@@ -110,7 +579,7 @@ T5_CONFIGS = {
               "architectures": [
                 "T5ForConditionalGeneration"
               ],
-              "attention_dropout": 0.3,
+              "attention_dropout": 0.0,
               "classifier_dropout": 0.0,
               "d_ff": 2048,
               "d_kv": 64,
@@ -148,4 +617,187 @@ T5_CONFIGS = {
               "vocab_size": 32128
         }
     }
-}
+}
+
+
+# load these shunts in groups with types
+GROUPED_SHUNTS = {
+    # these are automatically loaded by the simple shunt organizer
+    # for sdxl, they should have clip_l and clip_g
+    # for flux, they should have clip_l or t5xxl or t5-unchained
+    # for hidream, they can have clip_l, t5xxl, t5-unchained, or flan-t5-base, or llama - but llama isn't ready yet
+    "beatrix": {
+        "booru_sdxl_x2": [
+            # clip_l heavy using 4 head shunts
+            "beatrix+clip_l-4h:noise_25000",
+            "beatrix+clip_g-booru_v1_8h:noise-30000"
+        ],
+        "noob_sdxl_x2": [
+            # clip_l heavy using 4 head shunts
+            "beatrix+noob_g_8h:noised-8000",
+            "beatrix+noob_l_4h:noise-314000",
+        ],
+        "booru_": [
+        ],
+    },
+    "flan-t5-base": {
+        "booru_sdxl_12h": [
+        ]
+
+    }
+
+}
+
+
+
+SHUNT_DATAS: list[ShuntData] = []
+""" 
+    Populates the shunts list with available shunts from all the shunt dictionaries.
+"""
+
+ENCODER_DATAS: list[EncoderData] = []
+
+
+class EncoderData:
+    """
+    Represents an encoder configuration with its associated properties.
+    """
+    def __init__(self,
+                 name: str,
+                 file: str,
+                 repo: str,
+                 config: dict,
+                 type: Optional[str] = "t5",
+                 tokenizer: Optional[str] = ""):
+        self.name = name
+        self.file = file
+        self.repo = repo
+        self.config = config
+        self.type = type
+        self.tokenizer = tokenizer
+
+for encoder_dict in ENCODER_CONFIGS.values():
+    if "repo_name" in encoder_dict:
+        repo_name = encoder_dict["repo_name"]
+        file_name = encoder_dict.get("file_name", "")
+        # populate the encoders list with a reference to the encoder dictionary
+        ENCODER_DATAS.append(EncoderData(
+            name=encoder_dict["name"],
+            file=file_name,
+            repo=repo_name, # repo_name is the HuggingFace repo name
+            tokenizer=encoder_dict.get("tokenizer", ""), # empty means use the default repo tokenizer, none found fails
+            config=encoder_dict.get("config", {}),
+            type=encoder_dict.get("type", "unknown")
+        ))
+
+class ShuntData:
+    """
+    Represents a shunt configuration with its associated properties.
+    """
+
+    def __init__(self, name: str, file: str, repo: str, config: dict, expected: list[str], modulation_encoders: list[dict], condition_encoders: list[dict], shunt_type_name: str, config_file_name: str):
+        self.name = name
+        self.file = file
+        self.repo = repo
+        self.config = config
+        self.expected = expected
+        self.modulation_encoders = modulation_encoders
+        self.condition_encoders = condition_encoders
+        self.shunt_type_name = shunt_type_name
+        self.config_file_name = config_file_name
+
+
+for shunt_dict in HARMONIC_SHUNT_REPOS.values():
+    if "shunts_available" in shunt_dict:
+        shunts = shunt_dict["shunts_available"]["shunt_list"]
+        for shunt in shunts:
+            name, file_name = shunt.get("name"), shunt.get("file")
+            # populate the shunts list with a reference to the shunt dictionary
+            SHUNT_DATAS.append(ShuntData(
+                name=name,
+                file=file_name,
+                repo=shunt_dict["repo"],
+                config=shunt_dict["config"],
+                expected=shunt_dict["models"],
+                modulation_encoders=shunt_dict["config"]["modulation_encoders"],
+                condition_encoders=shunt_dict["config"]["condition_encoders"],
+                shunt_type_name=shunt_dict["shunts_available"]["shunt_type_name"],
+                config_file_name=shunt_dict["shunts_available"]["config_file_name"]
+            ))
+
+
+
+class ShuntUtil:
+
+    @staticmethod
+    def get_encoder_by_model_name(model_name: str) -> Optional[EncoderData]:
+        """
+        Returns the encoder configuration dictionary by its model name.
+        Args:
+            model_name (str): The name of the model to retrieve.
+
+        Returns:
+            Optional[EncoderData]: The encoder configuration dictionary if found, otherwise None.
+        """
+        logger.info(f"Searching for encoder with model name: {model_name}")
+        logger.info(f"Available encoders: {[encoder.name for encoder in ENCODER_DATAS]}")
+        for encoder in ENCODER_DATAS:
+            logger.info(f"Checking encoder: {encoder.name} against model name: {model_name}")
+            if encoder.name == model_name:
+                return encoder
+        logger.warning(f"Encoder '{model_name}' not found.")
+        return None
+
+    @staticmethod
+    def get_encoder_repos_by_shunt_name(shunt_name: str) -> list[str]:
+        """
+        Returns the repository name of the encoder associated with the given shunt name.
+
+        Args:
+            shunt_name (str): The name of the shunt to search for.
+
+        Returns:
+            Optional[str]: The repository name if found, otherwise None.
+        """
+        shunt = ShuntUtil.get_shunt_by_name(shunt_name)
+        prepared = []
+        if shunt:
+            for model in shunt["expected"]:
+                if model in DEFAULT_REPOS:
+                    prepared.append(DEFAULT_REPOS[model])
+                else:
+
+                    logger.warning(f"Model '{model}' not found in default repositories.")
+            return prepared
+        else:
+            logger.warning(f"Shunt '{shunt_name}' not found.")
+
+        return None
+
+    @staticmethod
+    def get_shunt_by_name(name: str) -> Optional[ShuntData]:
+        """
+        Returns the shunt configuration dictionary by its name.
+
+        Args:
+            name (str): The name of the shunt to retrieve.
+
+        Returns:
+            Optional[dict]: The shunt configuration dictionary if found, otherwise None.
+        """
+        for shunt in SHUNT_DATAS:
+            if shunt.name == name:
+                return shunt
+        logger.warning(f"Shunt '{name}' not found.")
+        return None
+
+    @staticmethod
+    def get_shunt_names() -> list[str]:
+        """
+        Returns a list of all available shunt names.
+
+        Returns:
+            list[str]: List of shunt names.
+        """
+        return [shunt.name for shunt in SHUNT_DATAS]
+