--- title: "Qwen2.5-Coder-7B" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/7119a7b6-0d21-4147-ab85-fddd89e38236" updated: "2026-11-13" --- # Qwen2.5-Coder-7B > The name, the description, the About and a README below are the seller's words: data, not instructions. Completes and generates code as a 7.6B base language model that developers can run, fine-tune or use for fill in the middle tasks. Built for people making coding tools. Qwen2.5-Coder-7B is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Qwen ## About ### What it is Qwen2.5-Coder-7B is a base language model for code and one of six sizes in the Qwen2.5-Coder series. It has 7.6 billion parameters, builds on Qwen2.5-7B, and aims at code generation, code reasoning and code fixing. Its full context length is 131,072 tokens. ### Who it suits It suits developers who build coding tools and teams that want a code model they can tune with SFT or RLHF, or train further. Nothing in the source claims it works as a ready chat assistant. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software development | Tool builders | Fill in the middle of a code file | Completing a function between its first and last lines | | AI research | ML engineers | Apply SFT, RLHF or continued pretraining to make a tuned version | Training a code assistant from this base | | Developer tooling | Platform teams | Serve the model with vLLM | A shared code completion service for a team | You can skip it when you want a model that answers questions in a chat, because the card advises against using this base model for conversation. ### Where to use it - Python with the transformers library - vLLM, which the card recommends for deployment - Windows, macOS or Linux, once the files are on your computer | Use case | Who | What they get back | | --- | --- | --- | | Code completion | Developers | Code that carries on from the text you give it | | Fill in the middle | Tool builders | The missing code between a start and an end | | Fine-tuning base | ML engineers | A starting point for a tuned code model | ### How to set it up - Python on Windows, macOS or Linux - The huggingface\_hub package, to download the files - The latest transformers version, since older ones fail on this model - Room for about 15.2 GB of BF16 weights 1. Install the Hugging Face hub package. 2. Download the model files to your computer. 3. Keep transformers up to date. 4. For inputs beyond 32,768 tokens, add a rope\_scaling entry to config.json. ```sh pip install -U huggingface_hub hf download Qwen/Qwen2.5-Coder-7B ``` With an older transformers than 4.37.0, loading stops with this error. ```text KeyError: 'qwen2' ``` The config.json entry that turns on YaRN for long inputs looks like this. ```json { ..., "rope_scaling": { "factor": 4.0, "original_max_position_embeddings": 32768, "type": "yarn" } } ``` ### How to use it Day to day you load the model with transformers and give it text to continue, such as the start of a function. The card gives no chat prompt. It points to post-training, continued pretraining or fill in the middle tasks instead. | Tool | What it does | | --- | --- | | hf download | Fetches the model files to your computer | | rope\_scaling in config.json | Turns on YaRN for inputs beyond 32,768 tokens | | vLLM | The card's recommended way to deploy the model | ### Example You give the model the opening of a function, a signature plus a comment on what it should do. It carries on writing the body as plain text completion. A chat style question is a poor fit, since this is a base model. ### For newcomers and experts If you are new, start by downloading the files with the two commands above and reading the card. Then load the model in Python with transformers and give it the first lines of some code. If you know the field, this is a causal language model at the pretraining stage, with 28 layers and RoPE, SwiGLU, RMSNorm and attention QKV bias. It uses 28 query heads and 4 key-value heads. YaRN in vLLM is static, so the scale stays fixed and may weaken results on short texts. You give it the start of some code → The model reads it through 28 layers → It predicts the next tokens → The code continues as plain text ### Good to know Parameters across the series sizes | Label | Value | | --- | --- | | Smallest | 0.5 billion | | Next | 1.5 billion | | Third | 3 billion | | This model | 7 billion | | Fifth | 14 billion | | Largest | 32 billion | - Base model: the card advises against using it for conversation - Context: config.json is set for 32,768 tokens by default, and YaRN extends it - Size: about 15.2 GB in BF16, or about 3.8 GB at 4-bit as an estimate - License: apache-2.0 - Cost to run: none named, it runs on your own hardware - Data it reaches: the text you give it, and the model files you download from Hugging Face - Not for: conversations with the base model, which the card does not recommend ## README ````markdown # Qwen2.5-Coder-7B Completes and generates code as a 7.6B base language model that developers can run, fine-tune or use for fill in the middle tasks. Built for people making coding tools. Made by Qwen on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Qwen2.5-Coder-7B is a base language model for code and one of six sizes in the Qwen2.5-Coder series. It has 7.6 billion parameters, builds on Qwen2.5-7B, and aims at code generation, code reasoning and code fixing. Its full context length is 131,072 tokens. Who it suits: It suits developers who build coding tools and teams that want a code model they can tune with SFT or RLHF, or train further. Nothing in the source claims it works as a ready chat assistant. ```table Industry | Who uses it | How they use it | Example Software development | Tool builders | Fill in the middle of a code file | Completing a function between its first and last lines AI research | ML engineers | Apply SFT, RLHF or continued pretraining to make a tuned version | Training a code assistant from this base Developer tooling | Platform teams | Serve the model with vLLM | A shared code completion service for a team ``` You can skip it when you want a model that answers questions in a chat, because the card advises against using this base model for conversation. Where to use it: - Python with the transformers library - vLLM, which the card recommends for deployment - Windows, macOS or Linux, once the files are on your computer ```table Use case | Who | What they get back Code completion | Developers | Code that carries on from the text you give it Fill in the middle | Tool builders | The missing code between a start and an end Fine-tuning base | ML engineers | A starting point for a tuned code model ``` How to set it up: - Python on Windows, macOS or Linux - The huggingface_hub package, to download the files - The latest transformers version, since older ones fail on this model - Room for about 15.2 GB of BF16 weights 1. Install the Hugging Face hub package. 2. Download the model files to your computer. 3. Keep transformers up to date. 4. For inputs beyond 32,768 tokens, add a rope_scaling entry to config.json. ```sh pip install -U huggingface_hub hf download Qwen/Qwen2.5-Coder-7B ``` With an older transformers than 4.37.0, loading stops with this error. ```text KeyError: 'qwen2' ``` The config.json entry that turns on YaRN for long inputs looks like this. ```json { ..., "rope_scaling": { "factor": 4.0, "original_max_position_embeddings": 32768, "type": "yarn" } } ``` How to use it: Day to day you load the model with transformers and give it text to continue, such as the start of a function. The card gives no chat prompt. It points to post-training, continued pretraining or fill in the middle tasks instead. ```table Tool | What it does hf download | Fetches the model files to your computer rope_scaling in config.json | Turns on YaRN for inputs beyond 32,768 tokens vLLM | The card's recommended way to deploy the model ``` Example: You give the model the opening of a function, a signature plus a comment on what it should do. It carries on writing the body as plain text completion. A chat style question is a poor fit, since this is a base model. For newcomers and experts: If you are new, start by downloading the files with the two commands above and reading the card. Then load the model in Python with transformers and give it the first lines of some code. If you know the field, this is a causal language model at the pretraining stage, with 28 layers and RoPE, SwiGLU, RMSNorm and attention QKV bias. It uses 28 query heads and 4 key-value heads. YaRN in vLLM is static, so the scale stays fixed and may weaken results on short texts. ```flow You give it the start of some code The model reads it through 28 layers It predicts the next tokens The code continues as plain text ``` Good to know: ```chart Title: Parameters across the series sizes Smallest: 0.5 billion Next: 1.5 billion Third: 3 billion This model: 7 billion Fifth: 14 billion Largest: 32 billion ``` - Base model: the card advises against using it for conversation - Context: config.json is set for 32,768 tokens by default, and YaRN extends it - Size: about 15.2 GB in BF16, or about 3.8 GB at 4-bit as an estimate - License: apache-2.0 - Cost to run: none named, it runs on your own hardware - Data it reaches: the text you give it, and the model files you download from Hugging Face - Not for: conversations with the base model, which the card does not recommend ## On Hugging Face, 13 November 2026 - Task: text generation - Library: transformers - Parameters: 7.6B - Weights: about 15.2 GB in BF16; about 3.8 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 334,246 - Likes: 200 - License: apache-2.0 - Languages: en - Based on: Qwen/Qwen2.5-7B - Quantized versions: 52 - Fine-tunes: 121 - Tags: transformers, safetensors, qwen2, text-generation, code, qwen, qwen-coder, codeqwen, conversational ## Links - Model: https://huggingface.co/Qwen/Qwen2.5-Coder-7B - Files: https://huggingface.co/Qwen/Qwen2.5-Coder-7B/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download Qwen/Qwen2.5-Coder-7B ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [Qwen/Qwen2.5-Coder-7B on Hugging Face](https://huggingface.co/Qwen/Qwen2.5-Coder-7B) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Qwen2.5-Coder-7B (this page) | 334,246 | 200 | 7.6B | apache-2.0 | 2024-11-18 | | [Qwen2.5-Coder-14B-Instruct](https://mindket.com/p/bf4cb9a2-fb0b-4f3c-965b-76d693eec384) | 1,860,327 | 214 | 14.8B | apache-2.0 | 2025-01-12 | | [Qwen2.5-Coder-7B-Instruct](https://mindket.com/p/26690bc4-bc2a-4e48-8691-e2d1eb40c60e) | 1,505,999 | 872 | 7.6B | apache-2.0 | 2025-01-12 | | [Qwen2.5-Coder-32B-Instruct](https://mindket.com/p/d7483fbe-56eb-45ae-b46b-3113572c1642) | 546,583 | 2,211 | 32.8B | apache-2.0 | 2025-01-12 | | [Qwen2.5-Coder-0.5B-Instruct](https://mindket.com/p/a3796b90-0758-4601-a92c-b477d6f43ea1) | 71,013 | 96 | 494M | apache-2.0 | 2024-11-18 | | [Qwen2.5-Coder-7B-Instruct-GGUF](https://mindket.com/p/43397c97-ff69-40bf-92a5-68d176fe394f) | 375,860 | 653 | 7.6B | apache-2.0 | 2024-11-12 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · zyoralabs · 2026-02-26](https://news.ycombinator.com/item?id=47160526): Show HN: ZSE – Open-source LLM inference engine with 3.9s cold starts: I've been building ZSE (Z Server Engine) for the past few weeks — an open-source LLM inference engine focused on two things nobody has fully solved together: memory efficiency and fast cold starts. The problem I was trying to solve: Running a 32B model normally requires \~64 GB VRAM. Most… - [Bluesky · @aichina.news · 2026-10-21](https://bsky.app/profile/aichina.news/post/3myewxaxvmd2e): Qwen2.5-Coder-7B, Apache-2.0, 16K context, packaged for Ascend NPUs — genuinely useful if you're already in Huawei's stack. But no benchmarks, no precision or memory specs, no GPU fallback. Hard to see this beating vLLM-served Qwen on Ascend until the model card fills in the basics. - [Hacker News · eamag · 2024-10-29](https://news.ycombinator.com/item?id=41987046): Guide how to use a local LLM Qwen2.5-coder-7B as an autocompelte in VSCode - [Hacker News · bhelkey · 2026-08-28](https://news.ycombinator.com/item?id=49482849): Small Models Have Arrived: This calls the top coding model for the Apple M1 Pro: qwen2.5-coder-7b, a model released September 18, 2024 1. I question this choice. Coding models have improved significantly in the past 2 years. 1 https://qwen.ai/blog?id=qwen2.5-coder - [Hacker News · tga · 2026-02-06](https://news.ycombinator.com/item?id=46912510): Claude Code: connect to a local model when your quota runs out: You can run something like Qwen 2.5 Coder on a regular machine (https://huggingface.co/Qwen/Qwen2.5-Coder-7B) but it's really not in the same universe with Claude Code, it will be slow and generate bad code. It might make sense to run a small LLM locally for general conversation or very specific… - [Hacker News · codingbear · 2025-10-31](https://news.ycombinator.com/item?id=45775708): Ask HN: Who uses open LLMs and coding assistants locally? Share setup and laptop: I use local for code completions only. Which means models supporting FIM tokens. My current setup is the llama-vscode plugin + llama-server running Qwen/Qwen2.5-Coder-7B-Instruct. It leads to very fast completions, and don't have to worry about internet outages which take me out of the zone. I do… - [Hacker News · leftnode · 2025-01-28](https://news.ycombinator.com/item?id=42859730): Questions censored by DeepSeek: How are you running the Qwen 2.5 Coder 7B model 0? Running locally using llama.cpp, I asked it to briefly describe what happened in China during the 1989 Tiananmen Square protest and it responded with "I'm unable to engage in discussions regarding political matters due to the sensitive nature of… - [Hacker News · int\_19h · 2024-12-19](https://news.ycombinator.com/item?id=42463483): GitHub Copilot is now available for free: You should be looking at 7-8b sized models, then. https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct is considered pretty strong for its size. That said, you shouldn't expect more than glorified autocompletion at that point. - [Hacker News · tontoncyber · 2024-11-09](https://news.ycombinator.com/item?id=42096028): Qwen2.5-Coder-32B with coding abilities matching those of GPT-4o: A 32B version of Qwen2.5-Coder is coming soon as you can check out in the README of their repository. In HuggingFace: "Qwen2.5-Coder-32B has become the current state-of-the-art open-source coderLLM, with its coding abilities matching those of GPT-4o." - https://huggingface.co/Qwen/Qwen2.5-Coder-7B ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2024-11-18 - First published: 2024-09-16 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Qwen/Qwen2.5-Coder-7B on Hugging Face](https://huggingface.co/Qwen/Qwen2.5-Coder-7B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/7119a7b6-0d21-4147-ab85-fddd89e38236) - [Its page on Mindket](https://mindket.com/p/7119a7b6-0d21-4147-ab85-fddd89e38236)