diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index a58528a0..b7067947 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -2,11 +2,13 @@ from modules import sd_samplers_kdiffusion, sd_samplers_timesteps, sd_samplers_l
 
 # imports for functions that previously were here and are used by other modules
 from modules.sd_samplers_common import samples_to_image_grid, sample_to_image  # noqa: F401
+from modules_forge import forge_alter_samplers
 
 all_samplers = [
     *sd_samplers_kdiffusion.samplers_data_k_diffusion,
     *sd_samplers_timesteps.samplers_data_timesteps,
     *sd_samplers_lcm.samplers_data_lcm,
+    *forge_alter_samplers.samplers_data_alter
 ]
 all_samplers_map = {x.name: x for x in all_samplers}
 
diff --git a/modules_forge/forge_alter_samplers.py b/modules_forge/forge_alter_samplers.py
new file mode 100644
index 00000000..eaef3551
--- /dev/null
+++ b/modules_forge/forge_alter_samplers.py
@@ -0,0 +1,40 @@
+import torch
+from modules import sd_samplers_kdiffusion, sd_samplers_common
+
+from ldm_patched.k_diffusion import sampling as k_diffusion_sampling
+from ldm_patched.modules.samplers import calculate_sigmas_scheduler
+
+
+class AlterSampler(sd_samplers_kdiffusion.KDiffusionSampler):
+    def __init__(self, sd_model, sampler_name, scheduler_name):
+        self.sampler_name = sampler_name
+        self.scheduler_name = scheduler_name
+        self.unet = sd_model.forge_objects.unet
+
+        sampler_function = getattr(k_diffusion_sampling, "sample_{}".format(sampler_name))
+        super().__init__(sampler_function, sd_model, None)
+
+    def get_sigmas(self, p, steps):
+        if self.scheduler_name == 'turbo':
+            timesteps = torch.flip(torch.arange(1, steps + 1) * float(1000.0 / steps) - 1, (0,)).round().long().clip(0, 999)
+            sigmas = self.unet.model.model_sampling.sigma(timesteps)
+            sigmas = torch.cat([sigmas, sigmas.new_zeros([1])])
+        else:
+            sigmas = calculate_sigmas_scheduler(self.unet.model, self.scheduler_name, steps)
+        return sigmas.to(self.unet.load_device)
+
+
+def build_constructor(sampler_name, scheduler_name):
+    def constructor(m):
+        return AlterSampler(m, sampler_name, scheduler_name)
+
+    return constructor
+
+
+samplers_data_alter = [
+    sd_samplers_common.SamplerData('DDPM', build_constructor(sampler_name='ddpm', scheduler_name='normal'), ['ddpm'], {}),
+    sd_samplers_common.SamplerData('DDPM Karras', build_constructor(sampler_name='ddpm', scheduler_name='karras'), ['ddpm_karras'], {}),
+    sd_samplers_common.SamplerData('DPM++ 2M Turbo', build_constructor(sampler_name='dpmpp_2m', scheduler_name='turbo'), ['dpmpp_2m_turbo'], {}),
+    sd_samplers_common.SamplerData('DPM++ 2M SDE Turbo', build_constructor(sampler_name='dpmpp_2m_sde', scheduler_name='turbo'), ['dpmpp_2m_sde_turbo'], {}),
+    sd_samplers_common.SamplerData('LCM Karras', build_constructor(sampler_name='lcm', scheduler_name='karras'), ['lcm_karras'], {}),
+]