diff --git a/CHANGELOG.md b/CHANGELOG.md
index 81486e925..07f916d52 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,10 +9,13 @@
     - `INT8` -> `uint8`  
     - `INT4_SYM` -> `int4`  
     - `INT4` -> `uint4`  
+  - Add `float8_e4m3fn` and `float8_e5m2` support  
   - Set the default quant mode to `pre`  
   - Use per token input quant with int8 matmul  
   - Implement better layer hijacks  
   - Fix Conv quant  
+  - Fix lora weight change  
+  - Use device_map = gpu  
 - **IPEX**  
   - Disabe Dynamic Attention by default on PyTorch 2.7  
   - Remove GradScaler hijack and use torch.amp.GradScaler instead  
diff --git a/modules/shared.py b/modules/shared.py
index 8fed9c635..cdb71534d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -525,7 +525,7 @@ options_templates.update(options_section(('quantization', "Quantization Settings
     "sdnq_quantize_sep": OptionInfo("<h2>SDNQ: SDNext Quantization</h2>", "", gr.HTML),
     "sdnq_quantize_weights": OptionInfo([], "Quantization enabled", gr.CheckboxGroup, {"choices": ["Model", "Transformer", "VAE", "TE", "Video", "LLM", "ControlNet"], "visible": native}),
     "sdnq_quantize_mode": OptionInfo("pre", "Quantization mode", gr.Dropdown, {"choices": ['pre', 'post'], "visible": native}),
-    "sdnq_quantize_weights_mode": OptionInfo("int8", "Quantization type", gr.Dropdown, {"choices": ['int8', 'uint4', "float8_e4m3fn", "float8_e5m2", 'uint8', 'int4'], "visible": native}),
+    "sdnq_quantize_weights_mode": OptionInfo("int8", "Quantization type", gr.Dropdown, {"choices": ['int8', 'uint4', "float8_e4m3fn", 'uint8', 'int4', "float8_e5m2"], "visible": native}),
     "sdnq_quantize_weights_group_size": OptionInfo(0, "Group size", gr.Slider, {"minimum": -1, "maximum": 4096, "step": 1, "visible": native}),
     "sdnq_quantize_conv_layers": OptionInfo(False, "Quantize the convolutional layers", gr.Checkbox, {"visible": native}),
     "sdnq_decompress_fp32": OptionInfo(False, "Decompress using full precision", gr.Checkbox, {"visible": native}),