What are the hardware requirements for Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed?

Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed requires approximately 2.2 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.

Where can I download or evaluate Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed?

Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed by PrunaAI — VRAM 2.2GB, 8K context

Name: Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed
Author: PrunaAI

Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed is an open-source language model by PrunaAI. Features: 2b LLM, VRAM: 2.2GB, Context: 8K, Quantized, LLM Explorer Score: 0.13.

4-bit 4bit Base model:cognitivecomputatio... Base model:quantized:cognitive... Bitsandbytes Gemma Pruna-ai Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/PrunaAI/cognitivecomputations-dolphin-2.8-gemma-2b-bnb-4bit-smashed

Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed Parameters and Internals

Model Type

causal_language_model

Use Cases

Primary Use Cases:

compression for cheaper, smaller, faster, greener AI models

Limitations:

Comparison results may vary depending on hardware, image size, batch size

Considerations:

Efficiency should be tested directly in use-case conditions.

Training Details

Data Sources:

WikiText

Methodology:

llm-int8

Input Output

Input Format:

Expected input in the form of text sequences tokenized using tokenizer.

Accepted Modalities:

text

Output Format:

Generates text sequences as output tokens.

Performance Tips:

Test the efficiency gains directly in your use-cases.

LLM Name	Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed
Repository 🤗	https://huggingface.co/PrunaAI/cognitivecomputations-dolphin-2.8-gemma-2b-bnb-4bit-smashed
Base Model(s)	cognitivecomputations/dolphin-2.8-gemma-2b cognitivecomputations/dolphin-2.8-gemma-2b
Model Size	2b
Required VRAM	2.2 GB
Updated	2025-09-23
Maintainer	PrunaAI
Model Type	gemma
Model Files	2.2 GB
Quantization Type	4bit
Model Architecture	GemmaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	float16

Rank the Cognitivecomputations Dolphin 2.8 Gemma 2B Bnb 4bit Smashed 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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Note: green Score (e.g. "73.2") means that the model is better than PrunaAI/cognitivecomputations-dolphin-2.8-gemma-2b-bnb-4bit-smashed.