[VLM] Add Nemotron-Nano-VL-8B-V1 support (#20349)
Signed-off-by: Kyle Huang <kylhuang@nvidia.com> Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com>
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@@ -429,6 +429,44 @@ def run_internvl(questions: list[str], modality: str) -> ModelRequestData:
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)
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# Nemontron_VL
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def run_nemotron_vl(questions: list[str], modality: str) -> ModelRequestData:
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model_name = "nvidia/Llama-3.1-Nemotron-Nano-VL-8B-V1"
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engine_args = EngineArgs(
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model=model_name,
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trust_remote_code=True,
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max_model_len=8192,
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limit_mm_per_prompt={modality: 1},
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)
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assert modality == "image"
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placeholder = "<image>"
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tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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messages = [
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[{"role": "user", "content": f"{placeholder}\n{question}"}]
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for question in questions
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]
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prompts = tokenizer.apply_chat_template(
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messages, tokenize=False, add_generation_prompt=True
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)
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# Stop tokens for InternVL
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# models variants may have different stop tokens
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# please refer to the model card for the correct "stop words":
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# https://huggingface.co/OpenGVLab/InternVL2-2B/blob/main/conversation.py
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stop_tokens = ["<|endoftext|>", "<|im_start|>", "<|im_end|>", "<|end|>"]
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stop_token_ids = [tokenizer.convert_tokens_to_ids(i) for i in stop_tokens]
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stop_token_ids = [token_id for token_id in stop_token_ids if token_id is not None]
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return ModelRequestData(
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engine_args=engine_args,
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prompts=prompts,
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stop_token_ids=stop_token_ids,
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)
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# Keye-VL
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def run_keye_vl(questions: list[str], modality: str) -> ModelRequestData:
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model_name = "Kwai-Keye/Keye-VL-8B-Preview"
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@@ -1186,6 +1224,7 @@ model_example_map = {
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"h2ovl_chat": run_h2ovl,
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"idefics3": run_idefics3,
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"internvl_chat": run_internvl,
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"nemotron_vl": run_nemotron_vl,
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"keye_vl": run_keye_vl,
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"kimi_vl": run_kimi_vl,
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"llava": run_llava,
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