From db1146f4e8d1d1a08380561b662c227076b4486d Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Thu, 3 Apr 2025 11:21:50 -0700
Subject: [PATCH] more qwen25vl

---
 convert/convert.go           |  2 +
 convert/convert_qwen25_vl.go | 81 ++++++++++++++++++++++++++++++++++++
 2 files changed, 83 insertions(+)
 create mode 100644 convert/convert_qwen25_vl.go

diff --git a/convert/convert.go b/convert/convert.go
index 63ff4003a..2a8689632 100644
--- a/convert/convert.go
+++ b/convert/convert.go
@@ -196,6 +196,8 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 		conv = &phi3Model{}
 	case "Qwen2ForCausalLM":
 		conv = &qwen2Model{}
+	case "Qwen2_5_VLForConditionalGeneration":
+		conv = &qwen25VLModel{}
 	case "Qwen2_5OmniModel":
 		conv = &qwen25OmniModel{}
 	case "BertModel":
diff --git a/convert/convert_qwen25_vl.go b/convert/convert_qwen25_vl.go
new file mode 100644
index 000000000..54812f303
--- /dev/null
+++ b/convert/convert_qwen25_vl.go
@@ -0,0 +1,81 @@
+package convert
+
+import (
+	"bytes"
+	"strings"
+
+	"github.com/ollama/ollama/fs/ggml"
+)
+
+type qwen25VLModel struct {
+	ModelParameters
+	HiddenSize            uint32  `json:"hidden_size"`
+	IntermediateSize      uint32  `json:"intermediate_size"`
+	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
+	NumAttentionHeads     uint32  `json:"num_attention_heads"`
+	HiddenLayers          uint32  `json:"num_hidden_layers"`
+	RopeTheta             float32 `json:"rope_theta"`
+	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
+	RMSNormEPS            float32 `json:"rms_norm_eps"`
+
+	VisionModel struct {
+	} `json:"vision_config"`
+}
+
+var _ ModelConverter = (*qwen25VLModel)(nil)
+
+func (q *qwen25VLModel) KV(t *Tokenizer) ggml.KV {
+	kv := q.ModelParameters.KV(t)
+	kv["general.architecture"] = "qwen25vl"
+	kv["qwen25vl.block_count"] = q.HiddenLayers
+	kv["qwen25vl.context_length"] = q.MaxPositionEmbeddings
+	kv["qwen25vl.embedding_length"] = q.HiddenSize
+	kv["qwen25vl.feed_forward_length"] = q.IntermediateSize
+	kv["qwen25vl.attention.head_count"] = q.NumAttentionHeads
+	kv["qwen25vl.attention.head_count_kv"] = q.NumKeyValueHeads
+	kv["qwen25vl.rope.freq_base"] = q.RopeTheta
+	kv["qwen25vl.attention.layer_norm_rms_epsilon"] = q.RMSNormEPS
+
+	return kv
+}
+
+func (q *qwen25VLModel) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor
+
+	for _, t := range ts {
+		if strings.HasSuffix(t.Name(), "patch_embed.proj.weight") {
+			var buf bytes.Buffer
+			t.WriteTo(&buf)
+			newTensors := splitPatchEmbed(buf, t.Kind(), t.Shape())
+			out = append(out, newTensors...)
+		} else {
+			out = append(out, ggml.Tensor{
+				Name:     t.Name(),
+				Kind:     t.Kind(),
+				Shape:    t.Shape(),
+				WriterTo: t,
+			})
+		}
+	}
+
+	return out
+}
+
+func (p *qwen25VLModel) Replacements() []string {
+	return []string{
+		"lm_head", "output",
+		"model.embed_tokens", "token_embd",
+		"model.layers", "blk",
+		"visual.blocks", "v.blk",
+		"input_layernorm", "attn_norm",
+		"self_attn.k_proj", "attn_k",
+		"self_attn.v_proj", "attn_v",
+		"self_attn.q_proj", "attn_q",
+		"self_attn.o_proj", "attn_output",
+		"mlp.down_proj", "ffn_down",
+		"mlp.gate_proj", "ffn_gate",
+		"mlp.up_proj", "ffn_up",
+		"post_attention_layernorm", "ffn_norm",
+		"model.norm", "output_norm",
+	}
+}