What are the hardware requirements for Refact 1 6B Fim?

Refact 1 6B Fim requires approximately 3.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Refact 1 6B Fim and how large is it?

Refact 1 6B Fim is developed by smallcloudai, a model with 6b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Refact 1 6B Fim perform on standard benchmarks?

Refact 1 6B Fim has the following published scores: HumanEval (Python) 31.1. Compare against reference models on this page or on the LLM Explorer leaderboards.

Refact 1 6B Fim by smallcloudai — VRAM 3.2GB

Name: Refact 1 6B Fim
Author: smallcloudai

Refact 1 6B Fim is an open-source language model by smallcloudai. Features: 6b LLM, VRAM: 3.2GB, License: bigscience-openrail-m, LLM Explorer Score: 0.12, HumanEval: 31.1.

Arxiv:1607.06450 Arxiv:1910.07467 Arxiv:1911.02150 Arxiv:2108.12409 Autotrain compatible Code Custom code Dataset:bigcode/commitpackft Dataset:bigcode/the-stack-dedu... Dataset:rombodawg/2xuncensored... En Gpt refact Model-index Pytorch Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/smallcloudai/Refact-1_6B-fim

Refact 1 6B Fim Parameters and Internals

LLM Name	Refact 1 6B Fim
Repository 🤗	https://huggingface.co/smallcloudai/Refact-1_6B-fim
Model Size	6b
Required VRAM	3.2 GB
Updated	2025-05-30
Maintainer	smallcloudai
Model Type	gpt_refact
Model Files	3.2 GB 3.2 GB
Supported Languages	en
Model Architecture	GPTRefactForCausalLM
License	bigscience-openrail-m
Transformers Version	4.31.0
Tokenizer Class	GPT2Tokenizer
Vocabulary Size	49216
Torch Data Type	bfloat16

Rank the Refact 1 6B Fim 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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