add AIBOM

Qwen_Qwen2.5-7B-Instruct.json

@@ -0,0 +1,69 @@
+{
+    "bomFormat": "CycloneDX",
+    "specVersion": "1.6",
+    "serialNumber": "urn:uuid:4ca2b6f8-6145-4d53-ae76-dc5fc7f694bb",
+    "version": 1,
+    "metadata": {
+        "timestamp": "2025-06-05T09:37:31.466856+00:00",
+        "component": {
+            "type": "machine-learning-model",
+            "bom-ref": "Qwen/Qwen2.5-7B-Instruct-0aa1dcca-35d6-540c-bb64-eb00402ee564",
+            "name": "Qwen/Qwen2.5-7B-Instruct",
+            "externalReferences": [
+                {
+                    "url": "https://huggingface.co/Qwen/Qwen2.5-7B-Instruct",
+                    "type": "documentation"
+                }
+            ],
+            "modelCard": {
+                "modelParameters": {
+                    "task": "text-generation",
+                    "architectureFamily": "qwen2",
+                    "modelArchitecture": "Qwen2ForCausalLM"
+                },
+                "properties": [
+                    {
+                        "name": "library_name",
+                        "value": "transformers"
+                    },
+                    {
+                        "name": "base_model",
+                        "value": "Qwen/Qwen2.5-7B"
+                    }
+                ]
+            },
+            "authors": [
+                {
+                    "name": "Qwen"
+                }
+            ],
+            "licenses": [
+                {
+                    "license": {
+                        "id": "Apache-2.0",
+                        "url": "https://spdx.org/licenses/Apache-2.0.html"
+                    }
+                }
+            ],
+            "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 7B Qwen2.5 model**, which has the following features:- Type: Causal Language Models- Training Stage: Pretraining & Post-training- Architecture: transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias- Number of Parameters: 7.61B- Number of Paramaters (Non-Embedding): 6.53B- Number of Layers: 28- Number of Attention Heads (GQA): 28 for Q and 4 for KV- Context Length: Full 131,072 tokens and generation 8192 tokens- Please refer to [this section](#processing-long-texts) for detailed instructions on how to deploy Qwen2.5 for handling long texts.For 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:2309.00071",
+                "arxiv:2407.10671",
+                "base_model:Qwen/Qwen2.5-7B",
+                "base_model:finetune:Qwen/Qwen2.5-7B",
+                "license:apache-2.0",
+                "autotrain_compatible",
+                "text-generation-inference",
+                "endpoints_compatible",
+                "region:us"
+            ]
+        }
+    }
+}