GPT-Neo
E435863
GPT-Neo is an open-source family of autoregressive language models developed by EleutherAI as a free alternative to OpenAI’s GPT-3.
All labels observed (5)
| Label | Occurrences |
|---|---|
| EleutherAI/gpt-neo | 1 |
| GPT-Neo canonical | 1 |
| GPT-Neo 1.3B | 1 |
| GPT-Neo 125M | 1 |
| GPT-Neo 2.7B | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4389188 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GPT-Neo Context triple: [Hugging Face Transformers, supportsModelType, GPT-Neo]
-
A.
GPT-2
GPT-2 is a large transformer-based language model known for generating coherent, human-like text and sparking widespread discussion about the implications of advanced AI text generation.
-
B.
GPT-3
GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
-
C.
GPT-3.5
GPT-3.5 is a large language model that generates human-like text and powers conversational AI applications such as advanced chatbots and coding assistants.
-
D.
Hugging Face Transformers
Hugging Face Transformers is a widely used open-source library that provides state-of-the-art transformer-based models and tools for natural language processing and related machine learning tasks.
-
E.
GPT-4
GPT-4 is a large multimodal language model known for its advanced reasoning, comprehension, and generation capabilities across text and images.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GPT-Neo Target entity description: GPT-Neo is an open-source family of autoregressive language models developed by EleutherAI as a free alternative to OpenAI’s GPT-3.
-
A.
GPT-2
GPT-2 is a large transformer-based language model known for generating coherent, human-like text and sparking widespread discussion about the implications of advanced AI text generation.
-
B.
GPT-3
GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
-
C.
GPT-3.5
GPT-3.5 is a large language model that generates human-like text and powers conversational AI applications such as advanced chatbots and coding assistants.
-
D.
Hugging Face Transformers
Hugging Face Transformers is a widely used open-source library that provides state-of-the-art transformer-based models and tools for natural language processing and related machine learning tasks.
-
E.
GPT-4
GPT-4 is a large multimodal language model known for its advanced reasoning, comprehension, and generation capabilities across text and images.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
autoregressive language model family
ⓘ
language model ⓘ language model ⓘ language model ⓘ open-source language model ⓘ |
| accessModel |
downloadable checkpoints
ⓘ
self-hosted ⓘ |
| architectureType | decoder-only transformer ⓘ |
| basedOn | transformer architecture ⓘ |
| compatibleWith | Hugging Face Transformers ⓘ |
| designedAs | free alternative to GPT-3 ⓘ |
| developer | EleutherAI ⓘ |
| framework |
PyTorch
ⓘ
TensorFlow ⓘ |
| hasCommunity | EleutherAI community ⓘ |
| hasModel |
GPT-Neo 1.3B
ⓘ
linked to:
GPT-Neo
GPT-Neo 125M ⓘ
linked to:
GPT-Neo
GPT-Neo 2.7B ⓘ
linked to:
GPT-Neo
|
| hostedOn | GitHub ⓘ |
| inspiredBy | GPT-3 ⓘ |
| language | English ⓘ |
| license | MIT License ⓘ |
| openSource | true ⓘ |
| parameterCount |
1.3 billion
ⓘ
125 million ⓘ 2.7 billion ⓘ |
| programmingLanguage | Python ⓘ |
| relatedTo |
GPT-J
ⓘ
GPT-NeoX-20B ⓘ |
| releasedBy | EleutherAI ⓘ |
| releaseYear | 2021 ⓘ |
| repositoryName |
EleutherAI/gpt-neo
ⓘ
linked to:
GPT-Neo
|
| supportsInference |
CPU
ⓘ
GPU ⓘ |
| supportsTask |
conditional text generation
ⓘ
few-shot learning ⓘ language modeling ⓘ text completion ⓘ text continuation ⓘ text generation ⓘ zero-shot learning ⓘ |
| tokenizerType | byte pair encoding ⓘ |
| trainingData | The Pile ⓘ |
| trainingDataDeveloper | EleutherAI ⓘ |
| trainingObjective | next token prediction ⓘ |
| trainingType | unsupervised learning ⓘ |
| useCase |
application integration
ⓘ
prototyping ⓘ research ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: GPT-Neo Description of subject: GPT-Neo is an open-source family of autoregressive language models developed by EleutherAI as a free alternative to OpenAI’s GPT-3.
Referenced by (5)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: GPT-Neo