What are the hardware requirements for Kittylm Qwen3 1.7B?

Kittylm Qwen3 1.7B requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Kittylm Qwen3 1.7B and how large is it?

Kittylm Qwen3 1.7B is developed by KittyLM, a model with 1.7b 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 Kittylm Qwen3 1.7B?

Kittylm Qwen3 1.7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Kittylm Qwen3 1.7B by KittyLM — VRAM 0.1GB

Name: Kittylm Qwen3 1.7B
Author: KittyLM

Kittylm Qwen3 1.7B is an open-source language model by KittyLM. Features: 1.7b LLM, VRAM: 0.1GB, License: apache-2.0, LLM Explorer Score: 0.31.

Base model:adapter:qwen/qwen3-... Base model:qwen/qwen3-1.7b Conversational Dataset:kittylm/kittylm-data Endpoints compatible Kittylm Lora Persona Qwen3 Region:us Roleplay Safetensors

Model Card on HF 🤗: https://huggingface.co/KittyLM/kittylm-qwen3-1.7b

Kittylm Qwen3 1.7B Parameters and Internals

LLM Name	Kittylm Qwen3 1.7B
Repository 🤗	https://huggingface.co/KittyLM/kittylm-qwen3-1.7b
Base Model(s)	Qwen/Qwen3-1.7B Qwen/Qwen3-1.7B
Model Size	1.7b
Required VRAM	0.1 GB
Updated	2026-10-01
Maintainer	KittyLM
Model Files	0.1 GB 3.4 GB
Model Architecture	AutoModelForCausalLM
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	down_proj\|v_proj\|up_proj\|o_proj\|gate_proj\|k_proj\|q_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	32
Errors	replace

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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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