What are the hardware requirements for Qwen25 1.5B Alpaca Id Sft?

Qwen25 1.5B Alpaca Id Sft requires approximately 3.1 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 Qwen25 1.5B Alpaca Id Sft and how large is it?

Qwen25 1.5B Alpaca Id Sft is developed by fathulhudoyo, a model with 1.5b 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 Qwen25 1.5B Alpaca Id Sft?

Qwen25 1.5B Alpaca Id Sft is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen25 1.5B Alpaca Id Sft by fathulhudoyo — VRAM 3.1GB, 32K context

Name: Qwen25 1.5B Alpaca Id Sft
Author: fathulhudoyo

Qwen25 1.5B Alpaca Id Sft is an open-source language model by fathulhudoyo. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.34.

4bit Conversational En Endpoints compatible Instruct Quantized Qwen2 Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/fathulhudoyo/qwen25-1.5b-alpaca-id-sft

Qwen25 1.5B Alpaca Id Sft Parameters and Internals

LLM Name	Qwen25 1.5B Alpaca Id Sft
Repository 🤗	https://huggingface.co/fathulhudoyo/qwen25-1.5b-alpaca-id-sft
Base Model(s)	unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-09-15
Maintainer	fathulhudoyo
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.1 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen25 1.5B Alpaca Id Sft 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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