From the model card
Fields below are copied from the tags and counters on the HuggingFace repository Qwen/Qwen2.5-7B-Instruct at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.
- Publisher (HF namespace)
- Qwen
- Pipeline tag
- text-generation
- Library
- Transformers
- Weight formats
- safetensors
- License tag
apache-2.0— read the license file in the repo before relying on it- Lineage
-
- base model Qwen/Qwen2.5-7B
- fine-tune of Qwen/Qwen2.5-7B
- Language tags
- English (en)
- Papers cited
- arXiv:2309.00071, arXiv:2407.10671
- Downloads (HF counter at last fetch)
- 10,684,701
- Likes (HF counter at last fetch)
- 1,576
- Model card
- https://huggingface.co/Qwen/Qwen2.5-7B-Instruct
Use cases
- Instruction-following tasks where 1-3B models fall short in reasoning depth
- Multilingual text generation and translation for supported languages
- Local LLM deployment on single-GPU workstations
- RAG pipeline generation where the generator needs stronger comprehension
- Code generation and explanation in supported programming languages
Pros
- Apache 2.0 license for unrestricted commercial use
- 7B scale provides significantly better reasoning than sub-3B models
- Multilingual capability across English and several other languages
- Text-generation-inference compatible for efficient batched serving
Cons
- 7B parameters require a GPU with 16GB+ VRAM for comfortable inference without quantization
- Qwen2.5 is superseded by Qwen3 series in the same family
- Instruction following still less reliable than models at 14B+ scale on complex tasks
- Knowledge cutoff limits utility for time-sensitive queries
- Quantized deployment reduces accuracy measurably on reasoning-heavy tasks
Tags
transformerssafetensorsqwen2text-generationchatconversationalenarxiv:2309.00071arxiv:2407.10671base_model:Qwen/Qwen2.5-7Bbase_model:finetune:Qwen/Qwen2.5-7Blicense:apache-2.0eval-resultstext-generation-inferenceendpoints_compatibledeploy:sagemakerdeploy:azureregion:us