What are the hardware requirements for PARM V2 Phi 4 4K CoT PyTorch?

PARM V2 Phi 4 4K CoT PyTorch requires approximately 29.4 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed PARM V2 Phi 4 4K CoT PyTorch and how large is it?

PARM V2 Phi 4 4K CoT PyTorch is developed by Pinkstack. 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 PARM V2 Phi 4 4K CoT PyTorch?

PARM V2 Phi 4 4K CoT PyTorch is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

PARM V2 Phi 4 4K CoT PyTorch by Pinkstack — VRAM 29.4GB, 16K context

Name: PARM V2 Phi 4 4K CoT PyTorch
Author: Pinkstack

PARM V2 Phi 4 4K CoT PyTorch is an open-source language model by Pinkstack. Features: LLM, VRAM: 29.4GB, Context: 16K, License: mit, Quantized, LLM Explorer Score: 0.16.

Arxiv:2412.08905 4bit Autotrain compatible Chat Code Conversational En Endpoints compatible Llama Math Phi Phi3 Pytorch Quantized Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/Pinkstack/PARM-V2-phi-4-4k-CoT-PyTorch

PARM V2 Phi 4 4K CoT PyTorch Parameters and Internals

LLM Name	PARM V2 Phi 4 4K CoT PyTorch
Repository 🤗	https://huggingface.co/Pinkstack/PARM-V2-phi-4-4k-CoT-PyTorch
Required VRAM	29.4 GB
Updated	2025-01-15
Maintainer	Pinkstack
Model Type	llama
Model Files	4.9 GB: 1-of-6 5.0 GB: 2-of-6 4.9 GB: 3-of-6 5.0 GB: 4-of-6 5.0 GB: 5-of-6 4.6 GB: 6-of-6
Supported Languages	en
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	mit
Context Length	16384
Model Max Length	16384
Transformers Version	4.47.1
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|dummy_87\|>
Vocabulary Size	100352
Torch Data Type	float16

Rank the PARM V2 Phi 4 4K CoT PyTorch 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

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... Text Chat 512K 6.0bpw H6 EXL2	512K / 5.2 GB	6	1
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... Text Chat 128K 6.0bpw H6 EXL2	128K / 5.2 GB	3	1
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...ocalAI Functioncall Phi 4 V0.3	16K / 29.4 GB	91	10
...ocalAI Functioncall Phi 4 V0.3	16K / 29.4 GB	6	8
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Note: green Score (e.g. "73.2") means that the model is better than Pinkstack/PARM-V2-phi-4-4k-CoT-PyTorch.