support LFM2-VL-450M

Author: tdakhran

convert_hf_to_gguf.py

@@ -8305,15 +8305,18 @@ class LFM2VLModel(MmprojModel):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         assert self.hparams_vision is not None
+        # TODO(tarek): for dynamic resolution image_size is not specified, setting here for compatibility
         self.hparams_vision["image_size"] = 256
 
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
         self.gguf_writer.add_clip_projector_type(gguf.VisionProjectorType.LFM2)
-        self.gguf_writer.add_vision_attention_layernorm_eps(self.hparams.get("layer_norm_eps", 1e-6))
-        self.gguf_writer.add_vision_projector_scale_factor(self.global_config.get("downsample_factor", 2))
+        self.gguf_writer.add_vision_attention_layernorm_eps(self.find_vparam(["layer_norm_eps"]))
+        self.gguf_writer.add_vision_projector_scale_factor(self.global_config.get("downsample_factor"))
         self.gguf_writer.add_vision_use_gelu(True)
-        self.gguf_writer.add_vision_block_count(self.find_vparam(self.n_block_keys) - 1)
+        # python notation, e.g. for vision_feature_layer == -1, we pick last layer -> vision_feature_layers_to_drop = 0
+        vision_feature_layers_to_drop = -(self.global_config.get("vision_feature_layer") + 1)
+        self.gguf_writer.add_vision_block_count(self.find_vparam(self.n_block_keys) - vision_feature_layers_to_drop)
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         del bid  # unused