What are the hardware requirements for Codegen 6B Mono Instruct Py Revised?

Codegen 6B Mono Instruct Py Revised requires approximately 28.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Codegen 6B Mono Instruct Py Revised and how large is it?

Codegen 6B Mono Instruct Py Revised is developed by dmayhem93, a model with 6b 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 Codegen 6B Mono Instruct Py Revised?

Codegen 6B Mono Instruct Py Revised is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Codegen 6B Mono Instruct Py Revised by dmayhem93 — VRAM 28.4GB

Name: Codegen 6B Mono Instruct Py Revised
Author: dmayhem93

Codegen 6B Mono Instruct Py Revised is an open-source language model by dmayhem93. Features: 6b LLM, VRAM: 28.4GB, Fine-Tuned, Instruction-Based, Code Generating, LLM Explorer Score: 0.05.

Codegen Endpoints compatible Finetuned Instruct Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/dmayhem93/codegen_6B_mono_instruct_py_revised

Codegen 6B Mono Instruct Py Revised Parameters and Internals

LLM Name	Codegen 6B Mono Instruct Py Revised
Repository 🤗	https://huggingface.co/dmayhem93/codegen_6B_mono_instruct_py_revised
Model Size	6b
Required VRAM	28.4 GB
Updated	2026-07-31
Maintainer	dmayhem93
Model Type	codegen
Instruction-Based	Yes
Model Files	9.9 GB: 1-of-3 9.8 GB: 2-of-3 8.7 GB: 3-of-3
Generates Code	Yes
Model Architecture	CodeGenForCausalLM
Transformers Version	4.26.0.dev0
Tokenizer Class	GPT2Tokenizer
Beginning of Sentence Token	<\|endoftext\|>
End of Sentence Token	<\|endoftext\|>
Unk Token	<\|endoftext\|>
Vocabulary Size	50297
Torch Data Type	float32
Activation Function	gelu_new
Errors	replace

Rank the Codegen 6B Mono Instruct Py Revised 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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