Principle:Axolotl ai cloud Axolotl Vision Language Model Loading

Knowledge Sources	LLaVA: Visual Instruction Tuning HuggingFace Vision Models Axolotl
Domains	Multimodal, Vision_Language, Model_Loading
Last Updated	2026-02-06 23:00 GMT

Overview

A model loading pattern that selects and instantiates the correct auto model class for vision-language architectures based on the model type.

Description

Vision-Language Model Loading extends standard model loading to handle multimodal architectures that process both images and text. Unlike text-only models that use AutoModelForCausalLM, vision-language models require AutoModelForImageTextToText or architecture-specific model classes.

The key challenge is model type detection: given a model name, automatically determining whether it's a vision-language model and selecting the correct auto model class. Axolotl maintains a MULTIMODAL_AUTO_MODEL_MAPPING that maps model types to their auto model classes, covering all HuggingFace MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING_NAMES plus custom entries for newer models.

Usage

Use vision-language model loading when:

• Fine-tuning vision-language models (LLaVA, Qwen2-VL, Pixtral, Llama Vision)
• The model config's model_type is in the multimodal mapping
• Training on image-text instruction pairs

Theoretical Basis

Vision-Language Model Architecture:

# Abstract VLM structure
class VisionLanguageModel:
    vision_encoder: ViT      # Processes images into embeddings
    projector: Linear         # Maps vision embeddings to LLM space
    language_model: LLM       # Generates text conditioned on vision+text

    def forward(self, pixel_values, input_ids):
        vision_features = self.vision_encoder(pixel_values)
        projected = self.projector(vision_features)
        # Interleave vision tokens with text tokens
        combined = interleave(projected, embed(input_ids))
        return self.language_model(combined)

Model type detection:

1. Check if model_type is in MULTIMODAL_AUTO_MODEL_MAPPING
2. If yes: use AutoModelForImageTextToText
3. If no: use AutoModelForCausalLM (standard text-only)

Related Pages

Implemented By

• Implementation:Axolotl_ai_cloud_Axolotl_ModelLoader_Load_Multimodal