What are the hardware requirements for Gpt2 124M Fineweb Edu?

Gpt2 124M Fineweb Edu requires approximately 0.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gpt2 124M Fineweb Edu and how large is it?

Gpt2 124M Fineweb Edu is developed by Anjaneyalu, a model with 124m 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 Gpt2 124M Fineweb Edu?

Gpt2 124M Fineweb Edu is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gpt2 124M Fineweb Edu by Anjaneyalu — VRAM 0.5GB

Name: Gpt2 124M Fineweb Edu
Author: Anjaneyalu

Gpt2 124M Fineweb Edu is an open-source language model by Anjaneyalu. Features: 124m LLM, VRAM: 0.5GB, License: apache-2.0, LLM Explorer Score: 0.29.

Dataset:huggingfacefw/fineweb-... En Endpoints compatible From-scratch Gpt2 Model-index Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Anjaneyalu/gpt2-124m-fineweb-edu

Gpt2 124M Fineweb Edu Parameters and Internals

LLM Name	Gpt2 124M Fineweb Edu
Repository 🤗	https://huggingface.co/Anjaneyalu/gpt2-124m-fineweb-edu
Model Size	124m
Required VRAM	0.5 GB
Updated	2026-10-25
Maintainer	Anjaneyalu
Model Type	gpt2
Model Files	0.5 GB
Supported Languages	en
Model Architecture	GPT2LMHeadModel
License	apache-2.0
Model Max Length	1024
Transformers Version	5.20.2
Tokenizer Class	GPT2Tokenizer
Vocabulary Size	50257
Activation Function	gelu_new
Errors	replace

Rank the Gpt2 124M Fineweb Edu 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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