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: 0.14.

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 Benchmarks

LLME Score: 0.1378

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Gemma 2 9B It Lora Yt Titles (AdamLucek/gemma-2-9b-it-lora-yt-titles)

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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	2026-05-20
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

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

Model	Likes	Downloads	VRAM
Gemma 2 9B 8bit	9	259	9 GB
Gemma 2 9B 4bit	2	172	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	7	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.

Rank the Gemma 2 9B It Lora Yt Titles Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20260328a

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Gemma 2 9B It Lora Yt Titles by AdamLucek