Add Gemma-4 to FORCE_FLOAT32 to prevent fp16 NaN in RL training

Gemma-4 produces NaN during GRPO training with dtype=torch.float16
due to torch.compile + fp16 autocast interaction in the backward pass.
Same class of issue as Gemma-3. Forces bfloat16 + float32 mixed
precision when users request fp16.

unsloth/models/loader.py

@@ -105,6 +105,8 @@ FORCE_FLOAT32 = [
     "gemma3,",  # Add comma bc gemma3 will match gemma3n
     "gemma3text",  # Gemma3TextModel (EmbeddingGemma, standalone text-only Gemma3)
     "gemma3n",
+    "gemma4,",  # Add comma bc gemma4 will match gemma4_text
+    "gemma4text",  # Gemma4TextModel (standalone text-only Gemma4)
     "gpt_oss",
     "qwen3_5",  # Qwen3.5 GDN layers produce NaN grad norms in float16 training
 ]