Support Qwen3

Author: CISC

convert_hf_to_gguf.py

@@ -2390,6 +2390,25 @@ def prepare_tensors(self):
                 raise ValueError(f"Unprocessed experts: {experts}")
 
 
+@Model.register("Qwen3ForCausalLM")
+class Qwen3Model(Model):
+    model_arch = gguf.MODEL_ARCH.QWEN3
+
+    def set_vocab(self):
+        try:
+            self._set_vocab_sentencepiece()
+        except FileNotFoundError:
+            self._set_vocab_gpt2()
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
+            if self.hparams["rope_scaling"].get("type") == "yarn":
+                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
+                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
+                self.gguf_writer.add_rope_scaling_orig_ctx_len(self.hparams["rope_scaling"]["original_max_position_embeddings"])
+
+
 @Model.register("GPT2LMHeadModel")
 class GPT2Model(Model):
     model_arch = gguf.MODEL_ARCH.GPT2