diff --git a/README.md b/README.md
index f2c588e1..ed754595 100644
--- a/README.md
+++ b/README.md
@@ -11,6 +11,7 @@ Inference of [Stable Diffusion](https://github.com/CompVis/stable-diffusion) in
 - Plain C/C++ implementation based on [ggml](https://github.com/ggerganov/ggml), working in the same way as [llama.cpp](https://github.com/ggerganov/llama.cpp)
 - Super lightweight and without external dependencies
 - SD1.x and SD2.x support
+- [SD-Turbo](https://huggingface.co/stabilityai/sd-turbo) support
 - 16-bit, 32-bit float support
 - 4-bit, 5-bit and 8-bit integer quantization support
 - Accelerated memory-efficient CPU inference
diff --git a/model.cpp b/model.cpp
index cfa58908..9eafd738 100644
--- a/model.cpp
+++ b/model.cpp
@@ -54,7 +54,6 @@ std::string self_attn_names[] = {
     "self_attn.q_proj.weight",
     "self_attn.k_proj.weight",
     "self_attn.v_proj.weight",
-
     "self_attn.q_proj.bias",
     "self_attn.k_proj.bias",
     "self_attn.v_proj.bias",
@@ -75,6 +74,8 @@ const char* unused_tensors[] = {
     "cond_stage_model.transformer.text_model.embeddings.position_ids",
     "cond_stage_model.model.logit_scale",
     "cond_stage_model.model.text_projection",
+    "conditioner.embedders.0.model.logit_scale",
+    "conditioner.embedders.0.model.text_projection",
     "model.diffusion_model.time_embedding.cond_proj.weight",
     "unet.time_embedding.cond_proj.weight",
     "model_ema.decay",
@@ -82,6 +83,7 @@ const char* unused_tensors[] = {
     "model_ema.diffusion_model",
     "control_model",
     "embedding_manager",
+    "denoiser.sigmas",
 };
 
 bool is_unused_tensor(std::string name) {
@@ -126,16 +128,19 @@ std::unordered_map<std::string, std::string> vae_decoder_name_map = {
 };
 
 std::string convert_open_clip_to_hf_clip(const std::string& name) {
-    std::string new_name                  = name;
+    std::string new_name = name;
+    if (starts_with(new_name, "conditioner.embedders.0.")) {
+        new_name = "cond_stage_model." + new_name.substr(strlen("conditioner.embedders.0."));
+    }
     std::string open_clip_resblock_prefix = "cond_stage_model.model.transformer.resblocks.";
     std::string hf_clip_resblock_prefix   = "cond_stage_model.transformer.text_model.encoder.layers.";
 
-    if (open_clip_to_hf_clip_model.find(name) != open_clip_to_hf_clip_model.end()) {
-        new_name = open_clip_to_hf_clip_model[name];
+    if (open_clip_to_hf_clip_model.find(new_name) != open_clip_to_hf_clip_model.end()) {
+        new_name = open_clip_to_hf_clip_model[new_name];
     }
 
-    if (name.find(open_clip_resblock_prefix) == 0) {
-        std::string remain = name.substr(open_clip_resblock_prefix.length());
+    if (new_name.find(open_clip_resblock_prefix) == 0) {
+        std::string remain = new_name.substr(open_clip_resblock_prefix.length());
         std::string idx    = remain.substr(0, remain.find("."));
         std::string suffix = remain.substr(idx.length() + 1);
 
@@ -349,7 +354,7 @@ std::string convert_diffusers_name_to_compvis(const std::string& key, char seq)
 
 std::string convert_tensor_name(const std::string& name) {
     std::string new_name;
-    if (starts_with(name, "cond_stage_model.model")) {
+    if (starts_with(name, "cond_stage_model.model") || starts_with(name, "conditioner.embedders.0.model")) {
         new_name = convert_open_clip_to_hf_clip(name);
     } else if (starts_with(name, "first_stage_model.decoder")) {
         new_name = convert_vae_decoder_name(name);
@@ -1159,7 +1164,8 @@ SDVersion ModelLoader::get_sd_version() {
         if (tensor_storage.name == "cond_stage_model.transformer.text_model.embeddings.token_embedding.weight" ||
             tensor_storage.name == "cond_stage_model.model.token_embedding.weight" ||
             tensor_storage.name == "text_model.embeddings.token_embedding.weight" ||
-            tensor_storage.name == "te.text_model.embeddings.token_embedding.weight") {
+            tensor_storage.name == "te.text_model.embeddings.token_embedding.weight" ||
+            tensor_storage.name == "conditioner.embedders.0.model.token_embedding.weight") {
             token_embedding_weight = tensor_storage;
             break;
         }