add AIBOM

AI-MO_NuminaMath-7B-TIR.json

@@ -0,0 +1,71 @@
+{
+    "bomFormat": "CycloneDX",
+    "specVersion": "1.6",
+    "serialNumber": "urn:uuid:6abaa880-fd87-409b-b3dd-f7017767e93d",
+    "version": 1,
+    "metadata": {
+        "timestamp": "2025-07-10T09:01:27.226304+00:00",
+        "component": {
+            "type": "machine-learning-model",
+            "bom-ref": "AI-MO/NuminaMath-7B-TIR-25bf135d-b699-508e-a81d-4ff4bb0efb1d",
+            "name": "AI-MO/NuminaMath-7B-TIR",
+            "externalReferences": [
+                {
+                    "url": "https://huggingface.co/AI-MO/NuminaMath-7B-TIR",
+                    "type": "documentation"
+                }
+            ],
+            "modelCard": {
+                "modelParameters": {
+                    "task": "text-generation",
+                    "architectureFamily": "llama",
+                    "modelArchitecture": "LlamaForCausalLM"
+                },
+                "properties": [
+                    {
+                        "name": "library_name",
+                        "value": "transformers"
+                    },
+                    {
+                        "name": "base_model",
+                        "value": "deepseek-ai/deepseek-math-7b-base"
+                    }
+                ],
+                "consideration": {
+                    "useCases": "Here's how you can run the model using the `pipeline()` function from \ud83e\udd17 Transformers:```pythonimport reimport torchfrom transformers import pipelinepipe = pipeline(\"text-generation\", model=\"AI-MO/NuminaMath-7B-TIR\", torch_dtype=torch.bfloat16, device_map=\"auto\")messages = [{\"role\": \"user\", \"content\": \"For how many values of the constant $k$ will the polynomial $x^{2}+kx+36$ have two distinct integer roots?\"},]prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)gen_config = {\"max_new_tokens\": 1024,\"do_sample\": False,\"stop_strings\": [\"```output\"], # Generate until Python code block is complete\"tokenizer\": pipe.tokenizer,}outputs = pipe(prompt, **gen_config)text = outputs[0][\"generated_text\"]print(text)"
+                }
+            },
+            "authors": [
+                {
+                    "name": "AI-MO"
+                }
+            ],
+            "licenses": [
+                {
+                    "license": {
+                        "id": "Apache-2.0",
+                        "url": "https://spdx.org/licenses/Apache-2.0.html"
+                    }
+                }
+            ],
+            "description": "- **Model type:** A 7B parameter math LLM fine-tuned in two stages of supervised fine-tuning, first on a dataset with math problem-solution pairs and then on a synthetic dataset with examples of multi-step generations using tool-integrated reasoning.- **Language(s) (NLP):** Primarily English- **License:** Apache 2.0- **Finetuned from model:** [deepseek-ai/deepseek-math-7b-base](https://huggingface.co/deepseek-ai/deepseek-math-7b-base)",
+            "tags": [
+                "transformers",
+                "safetensors",
+                "llama",
+                "text-generation",
+                "alignment-handbook",
+                "generated_from_trainer",
+                "conversational",
+                "arxiv:2309.17452",
+                "base_model:deepseek-ai/deepseek-math-7b-base",
+                "base_model:finetune:deepseek-ai/deepseek-math-7b-base",
+                "license:apache-2.0",
+                "autotrain_compatible",
+                "text-generation-inference",
+                "endpoints_compatible",
+                "region:us"
+            ]
+        }
+    }
+}