GPT-Neo-2.7B (finetuned)
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- EleutherAI
- Organisation type
- Research collective
- Country
- United States of America
- Published
- 21 March 2021
- Authors
- Sid Black, Leo Gao, Phil Wang, Connor Leahy, Stella Biderman
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation
- Base model
- GPT-Neo-2.7B
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Parameters
- 2.7B
- Training data
- tokens
- Epochs
- 1
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Open source
MIT. don't think model weights for finetune are available: https://github.com/EleutherAI/gpt-neo
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
- Citations
- 880
- Benchmark data
- GPT-Neo-2.7B (finetuned)
Sources
Where this record came from and when it was last checked.
- Reference
- GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow
- Last updated
- 11 February 2026
What the numbers mean
What this model is
GPT-Neo-2.7B (finetuned) was published by EleutherAI, in United States of America, in March 2021. It comes out of research collective.
It works in Language, and is recorded as doing language modeling/generation.
It builds on GPT-Neo-2.7B, which is why it shares that model's general shape and size.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
GPT-Neo-2.7B (finetuned) — common questions
Is GPT-Neo-2.7B (finetuned) open source?
No. GPT-Neo-2.7B (finetuned) has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does GPT-Neo-2.7B (finetuned) have?
GPT-Neo-2.7B (finetuned) has 2.7B parameters. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Who created GPT-Neo-2.7B (finetuned)?
GPT-Neo-2.7B (finetuned) was published by EleutherAI, based in United States of America, categorised as research collective.
When was GPT-Neo-2.7B (finetuned) released?
GPT-Neo-2.7B (finetuned) was published in March 2021. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is GPT-Neo-2.7B (finetuned) used for?
GPT-Neo-2.7B (finetuned) works in Language, and is recorded as handling language modeling/generation. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run GPT-Neo-2.7B (finetuned)?
None. GPT-Neo-2.7B (finetuned) is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.