What are the hardware requirements for Pythia 410M Deduped SimPOW 0?

Pythia 410M Deduped SimPOW 0 requires approximately 0.8 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 Pythia 410M Deduped SimPOW 0 and how large is it?

Pythia 410M Deduped SimPOW 0 is developed by RAY2L, a model with 410m 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 Pythia 410M Deduped SimPOW 0?

Pythia 410M Deduped SimPOW 0 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Pythia 410M Deduped SimPOW 0 by RAY2L — VRAM 0.8GB, 2K context

Name: Pythia 410M Deduped SimPOW 0
Author: RAY2L

Pythia 410M Deduped SimPOW 0 is an open-source language model by RAY2L. Features: 410m LLM, VRAM: 0.8GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.13.

Alignment-handbook Base model:eleutherai/pythia-4... Base model:finetune:eleutherai... Dataset:princeton-nlp/llama3-u... Endpoints compatible Generated from trainer Gpt neox Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/RAY2L/pythia-410m-deduped-SimPOW-0

Pythia 410M Deduped SimPOW 0 Parameters and Internals

Training Details

Data Sources:

princeton-nlp/llama3-ultrafeedback

LLM Name	Pythia 410M Deduped SimPOW 0
Repository 🤗	https://huggingface.co/RAY2L/pythia-410m-deduped-SimPOW-0
Base Model(s)	Pythia 410M Deduped EleutherAI/pythia-410m-deduped
Model Size	410m
Required VRAM	0.8 GB
Updated	2026-08-02
Maintainer	RAY2L
Model Type	gpt_neox
Model Files	0.8 GB 0.0 GB
Model Architecture	GPTNeoXForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.42.3
Tokenizer Class	GPTNeoXTokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	50304
Torch Data Type	bfloat16

Rank the Pythia 410M Deduped SimPOW 0 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

Best Alternatives to Pythia 410M Deduped SimPOW 0

Best Alternatives	Context / RAM	Downloads	Likes
...thia 410M Cell Type Prediction	4K / 0 GB	366	10
Pythia 410M	2K / 0.9 GB	261700	39
Pythia 410M Sft Full	2K / 0.8 GB	4	1
Pythia 410M Deduped	2K / 0.9 GB	62597	22
Pythia410m Sft Tldr	2K / 1.6 GB	7159	0
Healix 410M	2K / 1.6 GB	88	0
Pythia 410M Orpo	2K / 1.6 GB	5	0
...7 Kl 01 Steps 12000 Rlhf Model	2K / 1.6 GB	8	0
Pythia 410M Ludii Sft	2K / 1.6 GB	7	0
... Llm Pythia 410M Pm Gen Ian Nd	2K / 1.6 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than RAY2L/pythia-410m-deduped-SimPOW-0.