What are the hardware requirements for AceCoder Qwen2.5 Coder 7B Base Rule?

AceCoder Qwen2.5 Coder 7B Base Rule requires approximately 15.2 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed AceCoder Qwen2.5 Coder 7B Base Rule and how large is it?

AceCoder Qwen2.5 Coder 7B Base Rule is developed by TIGER-Lab, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate AceCoder Qwen2.5 Coder 7B Base Rule?

AceCoder Qwen2.5 Coder 7B Base Rule is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

AceCoder Qwen2.5 Coder 7B Base Rule by TIGER-Lab — VRAM 15.2GB, 32K context

Name: AceCoder Qwen2.5 Coder 7B Base Rule
Author: TIGER-Lab

AceCoder Qwen2.5 Coder 7B Base Rule is an open-source language model by TIGER-Lab. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: mit, Code Generating, LLM Explorer Score: 0.22.

Arxiv:2502.01718 Acecoder Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-coder-... Code Codegen Dataset:tiger-lab/acecode-87k En Qwen Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TIGER-Lab/AceCoder-Qwen2.5-Coder-7B-Base-Rule

AceCoder Qwen2.5 Coder 7B Base Rule Parameters and Internals

LLM Name	AceCoder Qwen2.5 Coder 7B Base Rule
Repository 🤗	https://huggingface.co/TIGER-Lab/AceCoder-Qwen2.5-Coder-7B-Base-Rule
Base Model(s)	Qwen/Qwen2.5-Coder-7B Qwen/Qwen2.5-Coder-7B
Model Size	7b
Required VRAM	15.2 GB
Updated	2025-09-23
Maintainer	TIGER-Lab
Model Type	qwen2
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Supported Languages	en
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the AceCoder Qwen2.5 Coder 7B Base Rule capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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