What are the hardware requirements for Gemma 2 9B Nopcsa Finetune?

Gemma 2 9B Nopcsa Finetune requires approximately 18.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 2 9B Nopcsa Finetune and how large is it?

Gemma 2 9B Nopcsa Finetune is developed by AndreasThinks, 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 Nopcsa Finetune?

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

Gemma 2 9B Nopcsa Finetune by AndreasThinks — VRAM 18.6GB

Name: Gemma 2 9B Nopcsa Finetune
Author: AndreasThinks

Gemma 2 9B Nopcsa Finetune is an open-source language model by AndreasThinks. Features: 9b LLM, VRAM: 18.6GB, License: gemma, Fine-Tuned, LLM Explorer Score: 0.13.

Autotrain compatible Base model:google/gemma-2-9b Conversational Endpoints compatible Finetuned Gemma2 Generated from trainer License:gemma Lora Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/AndreasThinks/gemma-2-9b-nopcsa-finetune

Gemma 2 9B Nopcsa Finetune Parameters and Internals

LLM Name	Gemma 2 9B Nopcsa Finetune
Repository 🤗	https://huggingface.co/AndreasThinks/gemma-2-9b-nopcsa-finetune
Base Model(s)	Gemma 2 9B google/gemma-2-9b
Model Size	9b
Required VRAM	18.6 GB
Updated	2024-07-21
Maintainer	AndreasThinks
Model Files	0.2 GB 4.9 GB: 1-of-4 5.0 GB: 2-of-4 5.0 GB: 3-of-4 3.7 GB: 4-of-4
Model Architecture	AutoModelForCausalLM
License	gemma
Is Biased	none
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|up_proj\|o_proj\|down_proj\|v_proj\|gate_proj\|k_proj
LoRA Alpha	16
LoRA Dropout	0.05
R Param	32

Rank the Gemma 2 9B Nopcsa Finetune capabilities

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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

Best Alternatives to Gemma 2 9B Nopcsa Finetune

Best Alternatives	Context / RAM	Downloads
ZYR3.1MoE	0K / 17.9 GB	259
Gemma 2 KoMed Lr2e 5	0K / 18.6 GB	22
MedGPT Gemma2 9B BA V.1	0K / 18.6 GB	7

Note: green Score (e.g. "73.2") means that the model is better than AndreasThinks/gemma-2-9b-nopcsa-finetune.