What are the hardware requirements for Ct2fast Pythia 12B Sft V8 7K Steps?

Ct2fast Pythia 12B Sft V8 7K Steps requires approximately 23.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Ct2fast Pythia 12B Sft V8 7K Steps and how large is it?

Ct2fast Pythia 12B Sft V8 7K Steps is developed by michaelfeil, a model with 12b 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 Pythia 12B Sft V8 7K Steps?

Ct2fast Pythia 12B Sft V8 7K Steps is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ct2fast Pythia 12B Sft V8 7K Steps by michaelfeil — VRAM 23.7GB

Name: Ct2fast Pythia 12B Sft V8 7K Steps
Author: michaelfeil

Ct2fast Pythia 12B Sft V8 7K Steps is an open-source language model by michaelfeil. Features: 12b LLM, VRAM: 23.7GB, License: apache-2.0, LLM Explorer Score: 0.07.

Ctranslate2 En Endpoints compatible Float16 - sft Int8 Region:us

Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-pythia-12b-sft-v8-7k-steps

Ct2fast Pythia 12B Sft V8 7K Steps Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

research, commercial applications

Additional Notes

Fast inference with Ctranslate2 using int8 and float16 quantization.

Supported Languages

en (proficient)

Training Details

Data Sources:

oasst_export, vicuna, dolly15k, grade_school_math_instructions, code_alpaca, red_pajama, wizardlm_70k, poem_instructions

Data Volume:

multiple datasets with varying val_split and fraction parameters

Methodology:

supervised fine-tuning

Context Length:

2048

Model Architecture:

Derived from OpenAssistant/pythia-12b-pre-v8-12.5k-steps

Input Output

Accepted Modalities:

text

Performance Tips:

Use 'device="cuda", compute_type="int8_float16"' for optimal CUDA performance.

LLM Name	Ct2fast Pythia 12B Sft V8 7K Steps
Repository 🤗	https://huggingface.co/michaelfeil/ct2fast-pythia-12b-sft-v8-7k-steps
Model Size	12b
Required VRAM	23.7 GB
Updated	2026-07-23
Maintainer	michaelfeil
Model Files	23.7 GB
Supported Languages	en
Model Architecture	AutoModel
License	apache-2.0
Tokenizer Class	GPTNeoXTokenizer

Rank the Ct2fast Pythia 12B Sft V8 7K Steps 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-pythia-12b-sft-v8-7k-steps.