{ "bomFormat": "CycloneDX", "specVersion": "1.6", "serialNumber": "urn:uuid:f24b7da0-02aa-40b9-97d8-8c76756a806e", "version": 1, "metadata": { "timestamp": "2025-06-05T09:37:34.037173+00:00", "component": { "type": "machine-learning-model", "bom-ref": "Qwen/Qwen3-4B-d504bcdf-8093-598c-937c-206e9c62b7df", "name": "Qwen/Qwen3-4B", "externalReferences": [ { "url": "https://huggingface.co/Qwen/Qwen3-4B", "type": "documentation" } ], "modelCard": { "modelParameters": { "task": "text-generation", "architectureFamily": "qwen3", "modelArchitecture": "Qwen3ForCausalLM" }, "properties": [ { "name": "library_name", "value": "transformers" }, { "name": "base_model", "value": "Qwen/Qwen3-4B-Base" } ] }, "authors": [ { "name": "Qwen" } ], "licenses": [ { "license": { "id": "Apache-2.0", "url": "https://spdx.org/licenses/Apache-2.0.html" } } ], "description": "**Qwen3-4B** has the following features:- Type: Causal Language Models- Training Stage: Pretraining & Post-training- Number of Parameters: 4.0B- Number of Paramaters (Non-Embedding): 3.6B- Number of Layers: 36- Number of Attention Heads (GQA): 32 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/).> [!TIP]> If you encounter significant endless repetitions, please refer to the [Best Practices](#best-practices) section for optimal sampling parameters, and set the ``presence_penalty`` to 1.5.", "tags": [ "transformers", "safetensors", "qwen3", "text-generation", "conversational", "arxiv:2309.00071", "arxiv:2505.09388", "base_model:Qwen/Qwen3-4B-Base", "base_model:finetune:Qwen/Qwen3-4B-Base", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ] } } }