add auraflow

modules/model_auraflow.py

@@ -0,0 +1,19 @@
+import torch
+import diffusers
+
+
+repo_id = 'fal/AuraFlow'
+
+
+def load_auraflow(_checkpoint_info, diffusers_load_config={}):
+    from modules import shared, devices
+    if 'torch_dtype' not in diffusers_load_config:
+        diffusers_load_config['torch_dtype'] = torch.float16
+
+    pipe = diffusers.AuraFlowPipeline.from_pretrained(
+        repo_id,
+        cache_dir = shared.opts.diffusers_dir,
+        **diffusers_load_config,
+    )
+    devices.torch_gc()
+    return pipe