What are the hardware requirements for Gemma 2 9B It Lora Yt Titles?

Gemma 2 9B It Lora Yt Titles requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 2 9B It Lora Yt Titles and how large is it?

Gemma 2 9B It Lora Yt Titles is developed by AdamLucek, a model with 9b 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 Gemma 2 9B It Lora Yt Titles?

Gemma 2 9B It Lora Yt Titles is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 2 9B It Lora Yt Titles by AdamLucek — VRAM 0.1GB

Name: Gemma 2 9B It Lora Yt Titles
Author: AdamLucek

Gemma 2 9B It Lora Yt Titles is an open-source language model by AdamLucek. Features: 9b LLM, VRAM: 0.1GB, License: gemma, LLM Explorer Score: 0.13.

Adapter Base model:adapter:google/gemm... Base model:google/gemma-2-9b-i... Conversational Dataset:adamlucek/youtube-titl... Finetuned Generated from trainer Lora Peft Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/AdamLucek/gemma-2-9b-it-lora-yt-titles

Gemma 2 9B It Lora Yt Titles Parameters and Internals

Model Type

text-generation

Use Cases

Primary Use Cases:

Generating YouTube titles similar to popular YouTubers

Training Details

Data Sources:

AdamLucek/youtube-titles

Methodology:

LoRA Adapters on Gemma-2-9B-IT for YouTube Titles fine-tuning

Context Length:

2048

Hardware Used:

single a6000 GPU

LLM Name	Gemma 2 9B It Lora Yt Titles
Repository 🤗	https://huggingface.co/AdamLucek/gemma-2-9b-it-lora-yt-titles
Base Model(s)	Gemma 2 9B It google/gemma-2-9b-it
Model Size	9b
Required VRAM	0.1 GB
Updated	2026-08-25
Maintainer	AdamLucek
Model Files	0.1 GB 0.0 GB
Model Architecture	Adapter
License	gemma
Is Biased	none
Tokenizer Class	GemmaTokenizer
Padding Token	<eos>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	v_proj\|o_proj\|q_proj\|k_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16

Rank the Gemma 2 9B It Lora Yt Titles 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

Quantized Models of the Gemma 2 9B It Lora Yt Titles

Model	Likes	Downloads	VRAM
Gemma 2 9B 8bit	9	178	9 GB
Gemma 2 9B 4bit	2	160	5 GB

Best Alternatives to Gemma 2 9B It Lora Yt Titles

Best Alternatives	Context / RAM	Downloads	Likes
...kish Lora Continue Pre Trained	0K / 0 GB	3	5
...emma9 On Korean Summary Events	0K / 0.2 GB	6	0
Yi 9B Booksum	0K / 0.2 GB	0	1
Yi 9B Booksum 2	0K / 0.9 GB	0	1
...escribe Diffusion Bf16 Adapter	0K / 0.1 GB	0	1

Note: green Score (e.g. "73.2") means that the model is better than AdamLucek/gemma-2-9b-it-lora-yt-titles.