What are the hardware requirements for Cognitivecomputations Dolphin 2 6 Phi 2 Bnb 4bit Smashed?

Cognitivecomputations Dolphin 2 6 Phi 2 Bnb 4bit Smashed requires approximately 1.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate Cognitivecomputations Dolphin 2 6 Phi 2 Bnb 4bit Smashed?

Cognitivecomputations Dolphin 2 6 Phi 2 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 6 Phi 2 Bnb 4bit Smashed by PrunaAI — VRAM 1.9GB

Name: Cognitivecomputations Dolphin 2 6 Phi 2 Bnb 4bit Smashed
Author: PrunaAI

Cognitivecomputations Dolphin 2 6 Phi 2 Bnb 4bit Smashed is an open-source language model by PrunaAI. Features: 1.6b LLM, VRAM: 1.9GB, Quantized, LLM Explorer Score: 0.13.

4-bit 4bit Base model:cognitivecomputatio... Base model:quantized:cognitive... Bitsandbytes Custom code Phi-msft Pruna-ai Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/PrunaAI/cognitivecomputations-dolphin-2_6-phi-2-bnb-4bit-smashed

Cognitivecomputations Dolphin 2 6 Phi 2 Bnb 4bit Smashed Parameters and Internals

Model Type

smashed, compressed

Use Cases

Areas:

commercial applications, research

Limitations:

Efficiency results may vary in other settings like different hardware or batch size., The model quality might vary from the base model.

Considerations:

We recommend testing efficiency gains directly in your use-cases.

Input Output

Input Format:

Text prompt input

Accepted Modalities:

text

Output Format:

Generated text

Performance Tips:

Run the model under use-case conditions to assess efficiency gains. Check 'first' and 'Sync'/'Async' metrics for specific contexts.

LLM Name	Cognitivecomputations Dolphin 2 6 Phi 2 Bnb 4bit Smashed
Repository 🤗	https://huggingface.co/PrunaAI/cognitivecomputations-dolphin-2_6-phi-2-bnb-4bit-smashed
Base Model(s)	Dolphin 2 6 Phi 2 cognitivecomputations/dolphin-2_6-phi-2
Model Size	1.6b
Required VRAM	1.9 GB
Updated	2025-09-23
Maintainer	PrunaAI
Model Type	phi-msft
Model Files	1.9 GB
Quantization Type	4bit
Model Architecture	PhiForCausalLM
Model Max Length	2048
Transformers Version	4.40.0
Tokenizer Class	CodeGenTokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	51200
Torch Data Type	float16
Activation Function	gelu_new

Rank the Cognitivecomputations Dolphin 2 6 Phi 2 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

Best Alternatives to Cognitivecomputations Dolphin 2 6 Phi 2 Bnb 4bit Smashed

Best Alternatives	Context / RAM	Downloads
Qlora4b Phi	2K / 2.5 GB	14
Qlora4b DPO	2K / 2.5 GB	13
...reamtobenlpsama Mcqa Quantized	2K / 1.8 GB	6
Phi 2 Voicechange	2K / 2.5 GB	6
Test Model	2K / 2.8 GB	0