Model reference · open weights

pythia-seed3

pythia-seed3 is an open-weight language model from EleutherAI, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

LLMs EleutherAI 2 variants 31k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What pythia-seed3 is

PolyPythias This model is part of the PolyPythias suite, an extension of the Pythia project providing 45 additional training runs across 5 model sizes with 9 different random seeds each. These models enable systematic study of training stability and reproducibility in language models. Paper PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs Oskar van der Wal, Pietro Lesci, Max Muller-Eberstein, Naomi Saphra, Hailey Schoelkopf, Willem Zuidema, and Stella Biderman. ICLR 2025. Model Details All models were trained on 300B tokens from The Pile. Naming Convention - pythia-{size}m - Original Pythia model (seed 1234) - pythia-{size}m-seed{1-9} - PolyPythias variants with different random seeds - pythia-160m-data-seed{1-3} - 160M models with only data ordering varied (weight init fixed) - pythia-160m-weight-seed{1-3} - 160M models with only weight initialization varied (data order fixed) The decoupled seed variants (data-seed and weight-seed) allow researchers to separately study the effects of data ordering vs. weight initialization. Quick Start Available Checkpoints Each model provides 154 intermediate checkpoints saved as Git branches: To load a specific checkpoint: Training Data All models were trained on The Pile using pre-shuffled data orderings. The shuffled index files for each seed are available at: EleutherAI/pile-preshuffled-seeds This dataset contains .idx files for seeds 0-9 used with MMapIndexedDataset to load the memory-mapped Pile data in the correct order for each seed. Reproducing Training Data Order To reproduce the exact data ordering used for a specific seed: 1. Download the Pile dataset and tokenize it using the Pythia tokenizer 2. Download the corresponding seed folder from pile-preshuffled-seeds: 3. Use the idx files with GPT-NeoX's MMapIndexedDataset: For complete training reproduction instructions, see the Pythia GitHub repository. All PolyPythias Models The complete collection is available at: EleutherAI/polypythias 14M Parameter Models - pythia-14m-seed1 through pythia-14m-seed9 31M Parameter Models - pythia-31m-seed1 through pythia-31m-seed9 70M Parameter Models - pythia-70m-seed1 through pythia-70m-seed9 160M

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

MakerEleutherAI
TypeLanguage models
Parameters (lead)213M
Context2k tokens
Variants2
Runs withtransformers
Released2023-02-15
Popularity31k downloads / month
LicenceOpen weights

How it works

How language models work

Your prompttext / messagesTransformerattention over tokensNext-token loopgenerate + streamResponsetext · tool callsA language model reads your tokens and predicts the next one, again and again, streaming the reply back.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
pythia-160m-seed3213MBF16~0.5 GBWeights ↗
pythia-410m-seed3BF16Weights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys pythia-seed3 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (pythia-seed3 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"pythia-seed3","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Languages

en

Trained / evaluated on

EleutherAI/pile EleutherAI/pile-preshuffled-seeds

Tags

transformers pytorch safetensors gpt_neox text-generation causal-lm pythia polypythias en dataset:EleutherAI/pile dataset:EleutherAI/pile-preshuffled-seeds text-generation-inference endpoints_compatible

Papers

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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