OpenCerebrum-1.0-7b-SFT-GGUF Open Source Model - Freely Support Multi-domain Text Generation and Q&A

Opencerebrum 1.0 7b SFT GGUF

Developed by mradermacher

OpenCerebrum-1.0-7b-SFT is a statically quantized model based on Locutusque/OpenCerebrum-1.0-7b-SFT, supporting multiple quantization versions, suitable for text generation and Q&A tasks in fields such as code generation, mathematics, chemistry, and biology.

Large Language Model Supports Multiple LanguagesOpen Source License:Apache-2.0 #Multidisciplinary Knowledge Q&A #Code Generation Optimization #Scientific Computing Support

Downloads 162

Release Time : 1/4/2025

Model Overview

This model is a supervised fine-tuned large language model that supports multiple quantization versions, suitable for text generation and Q&A tasks in code generation, mathematical problem-solving, chemistry, and biology.

Model Features

Multi-domain Support

The model performs excellently in multiple domains such as code generation, mathematics, chemistry, and biology.

Multiple Quantization Versions

Offers various quantization versions from Q2_K to f16 to meet different scenario requirements.

High-Quality Quantization

IQ quantization versions typically outperform non-IQ quantization versions of similar sizes, providing better performance and quality.

Model Capabilities

Text generation

Q&A

Code generation

Mathematical problem-solving

Chemistry problem-solving

Biology problem-solving

Use Cases

Education

Mathematical Problem-Solving

Solve complex mathematical problems, including algebra, geometry, etc.

Chemistry Problem-Solving

Answer chemistry-related questions, including chemical reactions, molecular structures, etc.

Programming

Code Generation

Generate Python code snippets based on descriptions.

Code Feedback

Provide feedback and improvement suggestions for code.

🚀 OpenCerebrum-1.0-7b-SFT Quantized Model

This project provides static quants of the OpenCerebrum-1.0-7b-SFT model. It offers a variety of quantized versions with different sizes and qualities, suitable for various usage scenarios.

🚀 Quick Start

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

✨ Features

Multi-Dataset Training: Trained on a diverse set of datasets covering multiple domains such as code, math, chemistry, biology, etc.
Multiple Quantized Versions: Provides a range of quantized versions with different sizes and qualities to meet different resource requirements.

📦 Installation

No specific installation steps are provided in the original document.

📚 Documentation

Model Information

Property	Details
Base Model	Locutusque/OpenCerebrum-1.0-7b-SFT
Datasets	Open-Orca/SlimOrca, glaiveai/glaive-code-assistant, camel-ai/physics, camel-ai/math, camel-ai/chemistry, camel-ai/biology, WizardLM/WizardLM_evol_instruct_V2_196k, microsoft/orca-math-word-problems-200k, grimulkan/theory-of-mind, Vezora/Tested-22k-Python-Alpaca, m-a-p/Code-Feedback, Locutusque/arc-cot, jondurbin/airoboros-2.1, WizardLM/WizardLM_evol_instruct_70k
Language	en
Library Name	transformers
License	apache-2.0
Quantized By	mradermacher
Tags	open-source, code, math, chemistry, biology, text-generation, question-answering

About

Static quants of https://huggingface.co/Locutusque/OpenCerebrum-1.0-7b-SFT. Weighted/imatrix quants are available at https://huggingface.co/mradermacher/OpenCerebrum-1.0-7b-SFT-i1-GGUF

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link	Type	Size/GB	Notes
GGUF	Q2_K	2.8
GGUF	Q3_K_S	3.3
GGUF	Q3_K_M	3.6	lower quality
GGUF	Q3_K_L	3.9
GGUF	IQ4_XS	4.0
GGUF	Q4_K_S	4.2	fast, recommended
GGUF	Q4_K_M	4.5	fast, recommended
GGUF	Q5_K_S	5.1
GGUF	Q5_K_M	5.2
GGUF	Q6_K	6.0	very good quality
GGUF	Q8_0	7.8	fast, best quality
GGUF	f16	14.6	16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

📄 License

This project is licensed under the apache-2.0 license.

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