What are the hardware requirements for Cognitivess?

Cognitivess requires approximately 11.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Cognitivess and how large is it?

Cognitivess is developed by CognitivessAI, a model with 8b 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 Cognitivess?

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

Cognitivess by CognitivessAI — VRAM 11.2GB

Name: Cognitivess
Author: CognitivessAI

Cognitivess is an open-source language model by CognitivessAI. Features: 8b LLM, VRAM: 11.2GB, License: apache-2.0, LLM Explorer Score: 0.13.

8-bit Autotrain compatible Cognitivess Conversational En Endpoints compatible Lora Model-index Peft Qlora Region:us Ro Safetensors Sentiment analysis Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/CognitivessAI/cognitivess

Cognitivess Parameters and Internals

LLM Name	Cognitivess
Repository 🤗	https://huggingface.co/CognitivessAI/cognitivess
Model Size	8b
Required VRAM	11.2 GB
Updated	2025-01-24
Maintainer	CognitivessAI
Model Type	CognitivessForCausalLM
Model Files	0.0 GB 5.0 GB: 1-of-3 4.1 GB: 2-of-3 2.1 GB: 3-of-3
Supported Languages	en ro
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Is Biased	none
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|eot_id\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|v_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16

Rank the Cognitivess 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

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Llama 3.1 8B Instuct Uz	128K / 16.1 GB	1000	15
Trillama 8B	8K / 16.1 GB	14	3
AutogenJune2000	8K / 33.8 GB	6	0
Llama3 8B	8K / 16.1 GB	7	0
NewMes V15	0K / 16.1 GB	409	18
Cve Model	0K / 0.3 GB	16	0
Shaista Pro	0K / 0 GB	10	0
...Datasets Layer 1 Decoder Fixed	0K / 0.7 GB	672	0
Medllama3 V20	0K / 16.1 GB	25328	78
ConfTuner Ministral	0K / 16.1 GB	13	4

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