EleutherAI / text-generation Open weights updated 3 years ago

pythia-160m-deduped

Name: pythia-160m-deduped
Author: EleutherAI

The Pythia Scaling Suite is a collection of models developed to facilitate interpretability research (see paper). It contains two sets of eight models of sizes 70M, 160M, 410M, 1B, 1.4B, 2.8B, 6.9B, and 12B. For each size, there are two models: one trained on the Pile, and one trained on the Pile after the dataset has been globally deduplicated. All 8 model sizes are trained on the exact same data, in the exact same...

Params

210 M

Context

2,048

Downloads 30d

145 K

Likes

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 103 days

▲ 102 K in the last 30 days (41.4%)

731 K138 K

Jul 31Sep 3Oct 7Nov 10

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	f16	0.4 GB	0.9 GB	✅ Runs comfortably

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub

~ · curl · api/v1

$ curl -s https://aimodelscomparison.com/api/v1/models/pythia-160m-deduped
{
  "hf_id": "EleutherAI/pythia-160m-deduped",
  "params_b": 0.21,
  "context_length": 2048,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 145007,
  "vram_estimates": [
    { "quant": "f16", "gb": 0.9 }
  ],
  "updated_at": "2026-07-31T01:00:38Z"
}

est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture: GPTNeoXForCausalLM
Parameters: 210 M
Tensor type: F16
Context length: 2,048
Vocabulary: 50,304
Layers / heads: 12 / 12
Licence: apache-2.0
First seen on the Hub: 2023-02-08
Training datasets: EleutherAI/the_pile_deduplicated
Added to our catalog: 2026-07-31

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