What are the hardware requirements for Running Coach Qwen3b Lora?

Running Coach Qwen3b Lora requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Running Coach Qwen3b Lora and how large is it?

Running Coach Qwen3b Lora is developed by hoodarunner, a model with 3b 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 Running Coach Qwen3b Lora?

Running Coach Qwen3b Lora is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Running Coach Qwen3b Lora by hoodarunner — VRAM 0.1GB

Name: Running Coach Qwen3b Lora
Author: hoodarunner

Running Coach Qwen3b Lora is an open-source language model by hoodarunner. Features: 3b LLM, VRAM: 0.1GB, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.28.

Adapter Base model:adapter:qwen/qwen2.... Base model:qwen/qwen2.5-3b-ins... Coaching Conversational Dataset:hoodarunner/running-co... En Finetuned Instruct Lora Peft Region:us Running Safetensors Sports-science

Model Card on HF 🤗: https://huggingface.co/hoodarunner/running-coach-qwen3b-lora

Running Coach Qwen3b Lora Parameters and Internals

LLM Name	Running Coach Qwen3b Lora
Repository 🤗	https://huggingface.co/hoodarunner/running-coach-qwen3b-lora
Base Model(s)	Qwen/Qwen2.5-3B-Instruct Qwen/Qwen2.5-3B-Instruct
Model Size	3b
Required VRAM	0.1 GB
Updated	2026-08-30
Maintainer	hoodarunner
Instruction-Based	Yes
Model Files	0.1 GB
Supported Languages	en
Model Architecture	Adapter
License	apache-2.0
Model Max Length	131072
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	gate_proj\|k_proj\|v_proj\|up_proj\|down_proj\|o_proj\|q_proj
LoRA Alpha	64
LoRA Dropout	0.05
R Param	32
Errors	replace

Rank the Running Coach Qwen3b Lora 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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