What are the hardware requirements for Indication PYT V2?

Indication PYT V2 requires approximately 5.7 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Indication PYT V2 and how large is it?

Indication PYT V2 is developed by Ketak-ZoomRx, a model with 2.8b 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 Indication PYT V2?

Indication PYT V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Indication PYT V2 by Ketak-ZoomRx — VRAM 5.7GB, 2K context

Name: Indication PYT V2
Author: Ketak-ZoomRx

Indication PYT V2 is an open-source language model by Ketak-ZoomRx. Features: 2.8b LLM, VRAM: 5.7GB, Context: 2K, LLM Explorer Score: 0.1.

Autotrain compatible En Gpt Gpt neox H2o-llmstudio Pytorch Region:us

Model Card on HF 🤗: https://huggingface.co/Ketak-ZoomRx/Indication_PYT_v2

Indication PYT V2 Parameters and Internals

Model Type

GPT, LLM, Large Language Model, h2o-llmstudio

Training Details

Methodology:

Model trained using H2O LLM Studio.

Model Architecture:

GPTNeoXForCausalLM

LLM Name	Indication PYT V2
Repository 🤗	https://huggingface.co/Ketak-ZoomRx/Indication_PYT_v2
Model Size	2.8b
Required VRAM	5.7 GB
Updated	2025-09-23
Maintainer	Ketak-ZoomRx
Model Type	gpt_neox
Model Files	5.7 GB
Supported Languages	en
Model Architecture	GPTNeoXForCausalLM
Context Length	2048
Model Max Length	2048
Transformers Version	4.29.2
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50304
Torch Data Type	float16

Rank the Indication PYT V2 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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Statichh Pythia 2.8B Sft Bf16	2K / 11.1 GB	8	0
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Hh Full	2K / 11.1 GB	6	0
... Llm Pythia 2.8B Pm Gen Ian Nd	2K / 11.1 GB	5	0
Pythia 2.8B Deduped	2K / 5.7 GB	8867	14
...thia 2.8B Mitchell Sft Hh Rlhf	2K / 11.1 GB	14	0
Pythia 2.8B Sft Hh Rlhf	2K / 5.6 GB	7	0
Pythia 2.8B	2K / 5.7 GB	45869	35
TLDR Pythia2.8B SFT	2K / 11.1 GB	7	0
...ythia 2.8B Helpful Sft 3epochs	2K / 5.6 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than Ketak-ZoomRx/Indication_PYT_v2.