[Model] Add Idefics3 support

docs/source/models/supported_models.rst

@@ -446,6 +446,12 @@ Text Generation
     - :code:`h2oai/h2ovl-mississippi-800m`, :code:`h2oai/h2ovl-mississippi-2b`, etc.
     - 
     - ✅︎
+  * - :code:`Idefics3ForConditionalGeneration`
+    - Idefics3
+    - T + I
+    - :code:`HuggingFaceM4/Idefics3-8B-Llama3` etc.
+    - 
+    - 
   * - :code:`InternVLChatModel`
     - InternVL2
     - T + I\ :sup:`E+`

examples/offline_inference_vision_language.py

@@ -377,6 +377,22 @@ def run_glm4v(question: str, modality: str):
     return llm, prompt, stop_token_ids
 
 
+# Idefics3-8B-Llama3
+def run_idefics3(question: str, modality: str):
+    assert modality == "image"
+    model_name = "HuggingFaceM4/Idefics3-8B-Llama3"
+
+    llm = LLM(model=model_name,
+              max_model_len=8192,
+              max_num_seqs=2,
+              enforce_eager=True)
+    prompt = (
+        f"<|begin_of_text|>User:<image>{question}<end_of_utterance>\nAssistant:"
+    )
+    stop_token_ids = None
+    return llm, prompt, stop_token_ids
+
+
 model_example_map = {
     "llava": run_llava,
     "llava-next": run_llava_next,
@@ -397,6 +413,7 @@ def run_glm4v(question: str, modality: str):
     "mllama": run_mllama,
     "molmo": run_molmo,
     "glm4v": run_glm4v,
+    "idefics3": run_idefics3,
 }
 
 

examples/offline_inference_vision_language_multi_image.py

@@ -290,6 +290,30 @@ def load_mllama(question, image_urls: List[str]) -> ModelRequestData:
     )
 
 
+def load_idefics3(question, image_urls: List[str]) -> ModelRequestData:
+    model_name = "HuggingFaceM4/Idefics3-8B-Llama3"
+
+    # The configuration below has been confirmed to launch on a single L40 GPU.
+    llm = LLM(
+        model=model_name,
+        max_model_len=8192,
+        max_num_seqs=16,
+        enforce_eager=True,
+        limit_mm_per_prompt={"image": len(image_urls)},
+    )
+
+    placeholders = "\n".join(f"Image-{i}: <image>\n"
+                             for i, _ in enumerate(image_urls, start=1))
+    prompt = f"<|begin_of_text|>User:{placeholders}\n{question}<end_of_utterance>\nAssistant:"  # noqa: E501
+    return ModelRequestData(
+        llm=llm,
+        prompt=prompt,
+        stop_token_ids=None,
+        image_data=[fetch_image(url) for url in image_urls],
+        chat_template=None,
+    )
+
+
 model_example_map = {
     "phi3_v": load_phi3v,
     "h2ovl_chat": load_h2onvl,
@@ -298,6 +322,7 @@ def load_mllama(question, image_urls: List[str]) -> ModelRequestData:
     "qwen2_vl": load_qwen2_vl,
     "qwen_vl_chat": load_qwenvl_chat,
     "mllama": load_mllama,
+    "idefics3": load_idefics3,
 }
 
 

tests/models/decoder_only/vision_language/test_models.py

@@ -327,6 +327,22 @@
         vllm_output_post_proc=model_utils.qwen_vllm_to_hf_output,
         prompt_path_encoder=model_utils.qwen_prompt_path_encoder,
     ),
+    "idefics3": VLMTestInfo(
+        models=["HuggingFaceM4/Idefics3-8B-Llama3"],
+        test_type=(VLMTestType.IMAGE, VLMTestType.MULTI_IMAGE),
+        prompt_formatter=lambda img_prompt:f"<|begin_of_text|>User:{img_prompt}<end_of_utterance>\nAssistant:",  # noqa: E501
+        img_idx_to_prompt=lambda idx: "<image>",
+        max_model_len=8192,
+        max_num_seqs=2,
+        auto_cls=AutoModelForVision2Seq,
+        marks=[
+            pytest.mark.skipif(
+                transformers.__version__ < "4.46.0",
+                reason="Model introduced in HF >= 4.46.0"
+            ),
+            large_gpu_mark(min_gb=48),
+        ],
+    ),
     ### Tensor parallel / multi-gpu broadcast tests
     "broadcast-chameleon": VLMTestInfo(
         models=["facebook/chameleon-7b"],

vllm/entrypoints/chat_utils.py

@@ -187,6 +187,8 @@ def _placeholder_str(self, modality: ModalityStr,
                 return "<|vision_start|><|image_pad|><|vision_end|>"
             if model_type == "molmo":
                 return ""
+            if model_type == "idefics3":
+                return "<image>"
 
             raise TypeError(f"Unknown {modality} model type: {model_type}")
         elif modality == "audio":

vllm/model_executor/models/idefics2_vision_model.py

@@ -15,7 +15,7 @@
 # limitations under the License.
 """PyTorch Idefics2 model."""
 
-from typing import Optional
+from typing import Iterable, Optional, Tuple
 
 import torch
 from torch import nn
@@ -29,6 +29,7 @@
                                                QKVParallelLinear,
                                                RowParallelLinear)
 from vllm.model_executor.layers.quantization import QuantizationConfig
+from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 
 class Idefics2VisionEmbeddings(nn.Module):
@@ -329,3 +330,25 @@ def forward(
         encoder_outputs = self.encoder(hidden_states)
         last_hidden_state = self.post_layernorm(encoder_outputs)
         return last_hidden_state
+
+    def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
+        stacked_params_mapping = [
+            # (param_name, shard_name, shard_id)
+            ("qkv_proj", "q_proj", "q"),
+            ("qkv_proj", "k_proj", "k"),
+            ("qkv_proj", "v_proj", "v"),
+        ]
+        params_dict = dict(self.named_parameters())
+        for name, loaded_weight in weights:
+            for param_name, weight_name, shard_id in stacked_params_mapping:
+                if weight_name not in name:
+                    continue
+                param = params_dict[name.replace(weight_name, param_name)]
+                weight_loader = param.weight_loader
+                weight_loader(param, loaded_weight, shard_id)
+                break
+            else:
+                param = params_dict[name]
+                weight_loader = getattr(param, "weight_loader",
+                                        default_weight_loader)
+                weight_loader(param, loaded_weight)