What are the hardware requirements for Balochi Qwen 2.5 7B Instruct?

Balochi Qwen 2.5 7B Instruct requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Balochi Qwen 2.5 7B Instruct and how large is it?

Balochi Qwen 2.5 7B Instruct is developed by umairjamali, 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 Balochi Qwen 2.5 7B Instruct?

Balochi Qwen 2.5 7B Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Balochi Qwen 2.5 7B Instruct by umairjamali — VRAM 0.2GB

Name: Balochi Qwen 2.5 7B Instruct
Author: umairjamali

Balochi Qwen 2.5 7B Instruct is an open-source language model by umairjamali. Features: 7b LLM, VRAM: 0.2GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.29.

Adapter Bal Balochi Base model:adapter:qwen/qwen2.... Base model:qwen/qwen2.5-7b-ins... Bcc Conversational Dataset:umairjamali/balochi-in... Finetuned Gguf Instruct Instruction-tuned Lora Quantized Qwen Qwen2.5 Region:us Safetensors Southern-balochi Unsloth

Model Card on HF 🤗: https://huggingface.co/umairjamali/balochi-qwen-2.5-7b-instruct

Balochi Qwen 2.5 7B Instruct Parameters and Internals

LLM Name	Balochi Qwen 2.5 7B Instruct
Repository 🤗	https://huggingface.co/umairjamali/balochi-qwen-2.5-7b-instruct
Base Model(s)	Qwen/Qwen2.5-7B-Instruct Qwen/Qwen2.5-7B-Instruct
Model Size	7b
Required VRAM	0.2 GB
Updated	2026-09-30
Maintainer	umairjamali
Instruction-Based	Yes
Model Files	0.2 GB 0.2 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Adapter
License	apache-2.0
Model Max Length	32768
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	down_proj\|o_proj\|v_proj\|up_proj\|q_proj\|k_proj\|gate_proj
LoRA Alpha	32
LoRA Dropout	0
R Param	16
Errors	replace

Rank the Balochi Qwen 2.5 7B Instruct 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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