{ "bomFormat": "CycloneDX", "specVersion": "1.6", "serialNumber": "urn:uuid:ba16e0ff-8444-4e79-81c9-9eea653ed07b", "version": 1, "metadata": { "timestamp": "2025-06-05T09:36:36.575018+00:00", "component": { "type": "machine-learning-model", "bom-ref": "Qwen/Qwen3-14B-e7db0982-cdda-5814-9807-f68f2876bf20", "name": "Qwen/Qwen3-14B", "externalReferences": [ { "url": "https://huggingface.co/Qwen/Qwen3-14B", "type": "documentation" } ], "modelCard": { "modelParameters": { "task": "text-generation", "architectureFamily": "qwen3", "modelArchitecture": "Qwen3ForCausalLM" }, "properties": [ { "name": "library_name", "value": "transformers" }, { "name": "base_model", "value": "Qwen/Qwen3-14B-Base" } ] }, "authors": [ { "name": "Qwen" } ], "licenses": [ { "license": { "id": "Apache-2.0", "url": "https://spdx.org/licenses/Apache-2.0.html" } } ], "description": "**Qwen3-14B** has the following features:- Type: Causal Language Models- Training Stage: Pretraining & Post-training- Number of Parameters: 14.8B- Number of Paramaters (Non-Embedding): 13.2B- Number of Layers: 40- Number of Attention Heads (GQA): 40 for Q and 8 for KV- Context Length: 32,768 natively and [131,072 tokens with YaRN](#processing-long-texts).For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our [blog](https://qwenlm.github.io/blog/qwen3/), [GitHub](https://github.com/QwenLM/Qwen3), and [Documentation](https://qwen.readthedocs.io/en/latest/).", "tags": [ "transformers", "safetensors", "qwen3", "text-generation", "conversational", "arxiv:2309.00071", "arxiv:2505.09388", "base_model:Qwen/Qwen3-14B-Base", "base_model:finetune:Qwen/Qwen3-14B-Base", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ] } } }