What are the hardware requirements for Qwen2.5 1.5B Instruct GccpSFT?

Qwen2.5 1.5B Instruct GccpSFT 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 Qwen2.5 1.5B Instruct GccpSFT and how large is it?

Qwen2.5 1.5B Instruct GccpSFT is developed by jyc0325, 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 Qwen2.5 1.5B Instruct GccpSFT?

Qwen2.5 1.5B Instruct GccpSFT is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 1.5B Instruct GccpSFT by jyc0325 — VRAM 3.1GB, 32K context

Name: Qwen2.5 1.5B Instruct GccpSFT
Author: jyc0325

Qwen2.5 1.5B Instruct GccpSFT is an open-source language model by jyc0325. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, Instruction-Based, LLM Explorer Score: 0.19.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-1.5b-i... Conversational Dataset:jyc0325/gcpp-50-50 Endpoints compatible Generated from trainer Instruct Open-r1 Qwen2 Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/jyc0325/Qwen2.5-1.5B-Instruct-gccpSFT

Qwen2.5 1.5B Instruct GccpSFT Parameters and Internals

LLM Name	Qwen2.5 1.5B Instruct GccpSFT
Repository 🤗	https://huggingface.co/jyc0325/Qwen2.5-1.5B-Instruct-gccpSFT
Model Name	Qwen2.5-1.5B-Instruct-gccpSFT
Base Model(s)	Qwen/Qwen2.5-1.5B-Instruct Qwen/Qwen2.5-1.5B-Instruct
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-07-26
Maintainer	jyc0325
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.1 GB 0.0 GB
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.52.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 1.5B Instruct GccpSFT capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Qwen2.5 1.5B Instruct GccpSFT

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 1.5B 1.3M Stretched	1280K / 3.1 GB	12	0
Merge Cord V1	128K / 3.1 GB	155	1
Gte Qwen2 1.5B Instruct	128K / 7.1 GB	1006596	237
AceInstruct 1.5B	128K / 3.5 GB	139	22
... Abliterated TIES Qwen2.5 1.5B	128K / 3.5 GB	15	0
Saba1 1.8B	128K / 3.6 GB	6	1
Miniclaus Qw1.5B UNAMGS	128K / 3.5 GB	12	8
Bellatrix 1.5B XElite	128K / 3.5 GB	19	3
GCIRS Reasoning 1.5B R1	128K / 3.5 GB	9	1
...illed Scout 1.5B Instruct Gen1	128K / 3.5 GB	10	0

Note: green Score (e.g. "73.2") means that the model is better than jyc0325/Qwen2.5-1.5B-Instruct-gccpSFT.