adding more loras

flux.2/config.yaml

@@ -69,7 +69,7 @@ config:
       train:
         batch_size: 2
         bypass_guidance_embedding: false
-        steps: 1500
+        steps: 2000
         gradient_accumulation: 1
         train_unet: true
         train_text_encoder: false
@@ -87,7 +87,7 @@ config:
           use_ema: false
           ema_decay: 0.99
         skip_first_sample: false
-        force_first_sample: false
+        force_first_sample: true
         disable_sampling: true
         dtype: "bf16"
         diff_output_preservation: false
@@ -119,7 +119,8 @@ config:
         sample_start_step: 0
         width: 1024
         height: 1024
-        samples: []
+        samples:
+          - prompt: "The photo of ISKA"
         neg: ""
         seed: 42
         walk_seed: true

flux.2/iska_flux2_000001600.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:127740b2a27d5710d06fcff0fbd707cc99986321368b9be281c8303c1f6eb40c
+size 97558704

flux.2/iska_flux2_000001700.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1c2260fb1588d5deb800911c28c041703d4a4731993cf4821e6bf26dfe2b911b
+size 97558704

flux.2/iska_flux2_000001800.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1fcf5de9625caae69e149ae02b2082d9328d906271862ebb21fc6bf6e08f28f7
+size 97558704

flux.2/iska_flux2_000001900.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:95317ed76b73631d3a8c29c36bf5a0b594079469d9340fd563ee19304408cfaf
+size 97558704

flux.2/iska_flux2_000002000.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:489bdfb1b0085c5fe4f8073d897321a65301794e5b4a1b8569cc4d0d11eb3c17
+size 97558704

scripts/check_if_lora_dead.py

@@ -0,0 +1,64 @@
+import torch
+from safetensors.torch import load_file
+ 
+def check_lora(file_path, threshold=1e-5):
+    """Check if a LoRA safetensors file contains dead (near-zero) weights."""
+    try:
+        sd = load_file(file_path)
+    except Exception as e:
+        print(f"❌ Could not load file: {e}")
+        return
+ 
+    # Collect all LoRA weight tensors (both A and B matrices)
+    lora_weights = []
+    for key, tensor in sd.items():
+        # Look for LoRA keys (adjust pattern if your trainer uses different naming)
+        if any(part in key.lower() for part in ['lora_a', 'lora_b', 'lora.']):
+            lora_weights.append(tensor)
+ 
+    if not lora_weights:
+        print("⚠️  No LoRA keys found in this file.")
+        print("   Could be a full model, or your trainer uses different naming.")
+        # Still check if *any* tensors are present
+        if sd:
+            print(f"   File contains {len(sd)} tensors. Example keys:")
+            for k in list(sd.keys())[:5]:
+                print(f"   - {k}")
+        return
+ 
+    # Combine all weights
+    all_weights = torch.cat([tensor.flatten() for tensor in lora_weights])
+ 
+    # Compute stats
+    max_abs = torch.max(torch.abs(all_weights)).item()
+    mean_abs = torch.mean(torch.abs(all_weights)).item()
+    num_zero = (all_weights == 0).sum().item()
+    total = all_weights.numel()
+ 
+    print(f"📊 LoRA tensor stats:")
+    print(f"   Total LoRA weights: {total}")
+    print(f"   Max absolute value: {max_abs:.6g}")
+    print(f"   Mean absolute value: {mean_abs:.6g}")
+    print(f"   Percentage exactly zero: {num_zero/total*100:.2f}%")
+    print(f"   Contains {len(lora_weights)} LoRA tensors.")
+ 
+    # Determine if dead
+    if max_abs < threshold:
+        print(f"\n❌ DEAD LORA: All weights are below {threshold}, effectively zero.")
+        print("   This was likely caused by `compile: true` — retrain without it.")
+    else:
+        print(f"\n✅ LoRA appears to have working weights (max abs > {threshold}).")
+        # Check for prefix issues
+        mangled_keys = [k for k in sd.keys() if '_orig_mod.' in k]
+        if mangled_keys:
+            print("   ⚠️  But keys contain '_orig_mod.' prefix — this might cause loading issues!")
+            print("   Example:", mangled_keys[0])
+        else:
+            print("   Keys look normal.")
+ 
+if __name__ == "__main__":
+    import sys
+    if len(sys.argv) != 2:
+        print("Usage: python check_lora.py <path_to_lora.safetensors>")
+        sys.exit(1)
+    check_lora(sys.argv[1])

scripts/test_flux.2_lora.py

@@ -0,0 +1,23 @@
+import os
+import fal_client
+import requests
+os.environ["FAL_KEY"] = "06ac9dcd-73fe-4799-9d80-9954eba39d84:f28d23d6abb91f26d2d337edc8cb9bf8"
+result = fal_client.subscribe(
+    "fal-ai/flux-2/lora",  # <-- Use FLUX.1 endpoint
+    arguments={
+        "prompt": "a photo of ISKA", # <-- Include trigger word
+        "loras": [
+            {
+                "path": "https://huggingface.co/YaroslavLinder/ISKA/resolve/main/flux.2/iska_flux2_000001500.safetensors",
+                "scale": 1.0
+            }
+        ],
+        "guidance_scale": 2.5,
+        "num_inference_steps": 28
+    }
+)
+print(result)
+output_url=result['images'][0]['url']
+response = requests.get(output_url)
+with open("output.png", "wb") as f:
+    f.write(response.content)