EleutherAI/pythia-70m-deduped

text-generation model by EleutherAI

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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 order. We also provide 154 intermediate checkpoints per model, hosted on Hugging Face as branches. The Pythia model suite was designed to promote scientific research on large language models, especially interpretability research. Despite not centering downstream performance as a design goal, we find the models match or exceed the performance of similar and same-sized models, such as those in the OPT and GPT-Neo suites. Details on previous early release and naming convention. Previously, we released an…

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Inside the original model card — Document outline
  1. Pythia-70M-deduped
  2. Model Details
  3. Uses and Limitations
  4. Intended Use
  5. Out-of-scope use
  6. Limitations and biases
  7. Quickstart
  8. Training
  9. Training data
  10. Training procedure
  11. Evaluations
  12. Changelog

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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

EleutherAI/pythia-70m-deduped is a text-generation model repository published by EleutherAI on Hugging Face. The source reports the transformers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
text-generation
Library
transformers
Recent downloads (30 days)
1,102,667
Cumulative likes
39
Hugging Face trending score
0
Reported safetensors parameters
95,592,496
Architecture
GPTNeoXForCausalLM
License
apache-2.0
Access
Not gated by Hugging Face
Created
2023-02-13T16:01:41.000Z
Last modified
2023-07-09T16:07:33.000Z

Compatibility and lineage

Reported languages: en

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Model card and usage instructions

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Source: Hugging Face Hub. Metadata observed 2026-11-01T06:51:29.042Z. Daily imports are snapshots, not real-time monitoring.

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