{
    "bomFormat": "CycloneDX",
    "specVersion": "1.6",
    "serialNumber": "urn:uuid:076b0dc2-9333-4f26-860f-8b81465eaffb",
    "version": 1,
    "metadata": {
        "timestamp": "2025-06-05T09:35:56.228809+00:00",
        "component": {
            "type": "machine-learning-model",
            "bom-ref": "Qwen/Qwen2.5-3B-Instruct-9e7eb871-9d9f-58d2-9da6-2f0ef8de7526",
            "name": "Qwen/Qwen2.5-3B-Instruct",
            "externalReferences": [
                {
                    "url": "https://huggingface.co/Qwen/Qwen2.5-3B-Instruct",
                    "type": "documentation"
                }
            ],
            "modelCard": {
                "modelParameters": {
                    "task": "text-generation",
                    "architectureFamily": "qwen2",
                    "modelArchitecture": "Qwen2ForCausalLM"
                },
                "properties": [
                    {
                        "name": "library_name",
                        "value": "transformers"
                    },
                    {
                        "name": "base_model",
                        "value": "Qwen/Qwen2.5-3B"
                    }
                ]
            },
            "authors": [
                {
                    "name": "Qwen"
                }
            ],
            "licenses": [
                {
                    "license": {
                        "name": "qwen-research",
                        "url": "https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE"
                    }
                }
            ],
            "description": "Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:- Significantly **more knowledge** and has greatly improved capabilities in **coding** and **mathematics**, thanks to our specialized expert models in these domains.- Significant improvements in **instruction following**, **generating long texts** (over 8K tokens), **understanding structured data** (e.g, tables), and **generating structured outputs** especially JSON. **More resilient to the diversity of system prompts**, enhancing role-play implementation and condition-setting for chatbots.- **Long-context Support** up to 128K tokens and can generate up to 8K tokens.- **Multilingual support** for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.**This repo contains the instruction-tuned 3B Qwen2.5 model**, which has the following features:- Type: Causal Language Models- Training Stage: Pretraining & Post-training- Architecture: transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias and tied word embeddings- Number of Parameters: 3.09B- Number of Paramaters (Non-Embedding): 2.77B- Number of Layers: 36- Number of Attention Heads (GQA): 16 for Q and 2 for KV- Context Length: Full 32,768 tokens and generation 8192 tokensFor more details, please refer to our [blog](https://qwenlm.github.io/blog/qwen2.5/), [GitHub](https://github.com/QwenLM/Qwen2.5), and [Documentation](https://qwen.readthedocs.io/en/latest/).",
            "tags": [
                "transformers",
                "safetensors",
                "qwen2",
                "text-generation",
                "chat",
                "conversational",
                "en",
                "arxiv:2407.10671",
                "base_model:Qwen/Qwen2.5-3B",
                "base_model:finetune:Qwen/Qwen2.5-3B",
                "license:other",
                "autotrain_compatible",
                "text-generation-inference",
                "endpoints_compatible",
                "region:us"
            ]
        }
    }
}