What are the hardware requirements for Geninstruct?

Geninstruct requires approximately 5.2 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Geninstruct and how large is it?

Geninstruct is developed by williamlcn, a model with 2.6b 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 Geninstruct?

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

Geninstruct by williamlcn — VRAM 5.2GB, 8K context

Name: Geninstruct
Author: williamlcn

Geninstruct is an open-source language model by williamlcn. Features: 2.6b LLM, VRAM: 5.2GB, Context: 8K, LLM Explorer Score: 0.17.

Arxiv:1910.09700 Conversational Endpoints compatible Gemma2 Llama-factory Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/williamlcn/geninstruct

Geninstruct Parameters and Internals

LLM Name	Geninstruct
Repository 🤗	https://huggingface.co/williamlcn/geninstruct
Model Size	2.6b
Required VRAM	5.2 GB
Updated	2026-07-06
Maintainer	williamlcn
Model Type	gemma2
Model Files	2.0 GB: 1-of-3 2.0 GB: 2-of-3 1.2 GB: 3-of-3
Model Architecture	Gemma2ForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.48.3
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Geninstruct 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 Geninstruct

Best Alternatives	Context / RAM	Downloads
Test	8K / 5.2 GB	33
SFT Peft	8K / 5.2 GB	12
SFT Fft	8K / 5.2 GB	8
Gemma 2 Full Dare Peft	8K / 10.5 GB	10
FFT Model Gemma	8K / 5.2 GB	7
Vera V1.1 Instruct	8K / 5.2 GB	12
SAFETY FULL FT VECTOR	8K / 10.5 GB	11
SAFETY PEFT VECTOR	8K / 10.5 GB	7
RESTA Sft Dare Full Ft	8K / 10.5 GB	5
Gemma2 DARE Sft Peft	8K / 10.5 GB	13

Note: green Score (e.g. "73.2") means that the model is better than williamlcn/geninstruct.