What are the hardware requirements for Reuters Gpt2 Text Gen?

Reuters Gpt2 Text Gen requires approximately 0.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Reuters Gpt2 Text Gen and how large is it?

Reuters Gpt2 Text Gen is developed by rebirthmonkey, a model with 125.8m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Reuters Gpt2 Text Gen?

Reuters Gpt2 Text Gen is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Reuters Gpt2 Text Gen by rebirthmonkey — VRAM 0.5GB

Name: Reuters Gpt2 Text Gen
Author: rebirthmonkey

Reuters Gpt2 Text Gen is an open-source language model by rebirthmonkey. Features: 125.8m LLM, VRAM: 0.5GB, License: mit, LLM Explorer Score: 0.2.

Base model:finetune:rebirthmon... Base model:rebirthmonkey/reute... Endpoints compatible Generated from trainer Gpt2 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/rebirthmonkey/reuters-gpt2-text-gen

Reuters Gpt2 Text Gen Parameters and Internals

LLM Name	Reuters Gpt2 Text Gen
Repository 🤗	https://huggingface.co/rebirthmonkey/reuters-gpt2-text-gen
Base Model(s)	Reuters Gpt2 Text Gen rebirthmonkey/reuters-gpt2-text-gen
Model Size	125.8m
Required VRAM	0.5 GB
Updated	2026-07-21
Maintainer	rebirthmonkey
Model Type	gpt2
Model Files	0.5 GB 0.0 GB
Model Architecture	GPT2LMHeadModel
License	mit
Model Max Length	1024
Transformers Version	4.55.0
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	52000
Torch Data Type	float32
Activation Function	gelu_new

Rank the Reuters Gpt2 Text Gen capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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