What are the hardware requirements for Terrible Joke Qwen3 1.7B?

Terrible Joke Qwen3 1.7B requires approximately 3.4 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Terrible Joke Qwen3 1.7B and how large is it?

Terrible Joke Qwen3 1.7B is developed by locriani, 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 Terrible Joke Qwen3 1.7B?

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

Terrible Joke Qwen3 1.7B by locriani — VRAM 3.4GB, 40K context

Name: Terrible Joke Qwen3 1.7B
Author: locriani

Terrible Joke Qwen3 1.7B is an open-source language model by locriani. Features: 1.7b LLM, VRAM: 3.4GB, Context: 40K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.3.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-1.7b Conversational En Endpoints compatible Humor Instruct Instruction-following Lora Lora-merged Qwen3 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/locriani/terrible-joke-qwen3-1.7b

Terrible Joke Qwen3 1.7B Parameters and Internals

LLM Name	Terrible Joke Qwen3 1.7B
Repository 🤗	https://huggingface.co/locriani/terrible-joke-qwen3-1.7b
Base Model(s)	Qwen/Qwen3-1.7B Qwen/Qwen3-1.7B
Model Size	1.7b
Required VRAM	3.4 GB
Updated	2026-11-01
Maintainer	locriani
Model Type	qwen3
Instruction-Based	Yes
Model Files	3.4 GB
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	5.21.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
LoRA Model	Yes
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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