What are the hardware requirements for Ct2fast GPT J 6B?

Ct2fast GPT J 6B requires approximately 12.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Ct2fast GPT J 6B and how large is it?

Ct2fast GPT J 6B is developed by michaelfeil, 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 Ct2fast GPT J 6B?

Ct2fast GPT J 6B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ct2fast GPT J 6B by michaelfeil — VRAM 12.1GB

Name: Ct2fast GPT J 6B
Author: michaelfeil

Ct2fast GPT J 6B is an open-source language model by michaelfeil. Features: 6b LLM, VRAM: 12.1GB, License: apache-2.0, LLM Explorer Score: 0.06.

Arxiv:2101.00027 Arxiv:2104.09864 Ctranslate2 Dataset:the pile En Endpoints compatible Float16 Int8 Pytorch Region:us

Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-gpt-j-6b

Ct2fast GPT J 6B Parameters and Internals

Model Type

text generation, causal-lm

Use Cases

Areas:

research, text generation applications

Applications:

text generation

Primary Use Cases:

Generating text from prompts

Limitations:

Not suitable for human-facing interactions without fine-tuning, May generate harmful or offensive text, Not suitable for language translation

Considerations:

Supervision and moderation recommended for outputs

Additional Notes

This is a quantized version optimized for fast inference.

Supported Languages

en (English - high proficiency)

Training Details

Data Sources:

the Pile

Data Volume:

402 billion tokens

Methodology:

Autoregressive language modeling

Context Length:

2048

Hardware Used:

TPU v3-256 pod

Model Architecture:

Transformer with 28 layers, 16 heads, 4096 dimensional model

Input Output

Input Format:

Text prompts

Accepted Modalities:

text

Output Format:

Text generation

Performance Tips:

Intended for int8_float16 quantization on CUDA

Release Notes

Version:

N/A

Date:

2023-05-19

Notes:

Converted to int8_float16 for fast inference on CUDA

LLM Name	Ct2fast GPT J 6B
Repository 🤗	https://huggingface.co/michaelfeil/ct2fast-gpt-j-6b
Model Size	6b
Required VRAM	12.1 GB
Updated	2026-08-07
Maintainer	michaelfeil
Model Files	12.1 GB
Supported Languages	en
Model Architecture	AutoModel
License	apache-2.0
Model Max Length	2048
Tokenizer Class	GPT2Tokenizer
Beginning of Sentence Token	<\|endoftext\|>
End of Sentence Token	<\|endoftext\|>
Unk Token	<\|endoftext\|>
Errors	replace

Rank the Ct2fast GPT J 6B capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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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Note: green Score (e.g. "73.2") means that the model is better than michaelfeil/ct2fast-gpt-j-6b.