What are the hardware requirements for Pythia 2.8B Deduped Rp 710M 4K?

Pythia 2.8B Deduped Rp 710M 4K requires approximately 11.7 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Pythia 2.8B Deduped Rp 710M 4K and how large is it?

Pythia 2.8B Deduped Rp 710M 4K is developed by emozilla, a model with 1b 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 2.8B Deduped Rp 710M 4K?

Pythia 2.8B Deduped Rp 710M 4K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Pythia 2.8B Deduped Rp 710M 4K by emozilla — VRAM 11.7GB, 4K context

Name: Pythia 2.8B Deduped Rp 710M 4K
Author: emozilla

Pythia 2.8B Deduped Rp 710M 4K is an open-source language model by emozilla. Features: 1b LLM, VRAM: 11.7GB, Context: 4K, LLM Explorer Score: 0.06.

Endpoints compatible Gpt neox Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/emozilla/pythia-2.8b-deduped-rp-710m-4k

Pythia 2.8B Deduped Rp 710M 4K Parameters and Internals

LLM Name	Pythia 2.8B Deduped Rp 710M 4K
Repository 🤗	https://huggingface.co/emozilla/pythia-2.8b-deduped-rp-710m-4k
Model Size	1b
Required VRAM	11.7 GB
Updated	2026-07-18
Maintainer	emozilla
Model Type	gpt_neox
Model Files	10.4 GB: 1-of-2 1.3 GB: 2-of-2
Model Architecture	GPTNeoXForCausalLM
Context Length	4096
Model Max Length	4096
Transformers Version	4.28.1
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50304
Torch Data Type	float32

Rank the Pythia 2.8B Deduped Rp 710M 4K 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 Pythia 2.8B Deduped Rp 710M 4K

Best Alternatives	Context / RAM	Downloads	Likes
C2S Scale Pythia 1B Pt	8K / 0 GB	259	9
Pythia 1.4B Deduped Rp 420M 4K	4K / 6.1 GB	11	1
Pythia 1.4B Deduped Rp 280M 4K	4K / 6.1 GB	9	1
Chatml Test	2K / 2.1 GB	15	0
Pythia 1B Kto Iter0	2K / 2 GB	12	0
Pythia 1B Self Kto Iter0	2K / 2 GB	9	0
...eduped Tldr Preference Sft Trl	2K / 2 GB	14	0
...rAI Pythia 1B Deduped Sft Tldr	2K / 4 GB	3896	0
Pythia 1B	2K / 2.1 GB	173161	45
Pythia 1B Deduped Tldr Sft	2K / 2 GB	162	0

Note: green Score (e.g. "73.2") means that the model is better than emozilla/pythia-2.8b-deduped-rp-710m-4k.