Goekdeniz-Guelmez/Josiefied-Qwen2.5-Coder-7B-Instruct-abliterated-v1

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Nov 19, 2024License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

Goekdeniz-Guelmez/Josiefied-Qwen2.5-Coder-7B-Instruct-abliterated-v1 is a 7.6 billion parameter instruction-tuned language model developed by Gökdeniz Gülmez, based on the Qwen2.5-Coder architecture. This model is specifically fine-tuned on a custom dataset for increased uncensoredness and is optimized for coding, software development, and technical problem-solving tasks. It functions as an unrestricted assistant, providing clear, precise, and effective assistance across various programming languages and frameworks, with a context length of 32768 tokens.

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Model Overview

Goekdeniz-Guelmez/Josiefied-Qwen2.5-Coder-7B-Instruct-abliterated-v1 is a 7.6 billion parameter instruction-tuned model developed by Gökdeniz Gülmez. It is built upon the Qwen/Qwen2.5-Coder-7B-Instruct base model and has been further fine-tuned on a custom dataset. The primary goal of this fine-tuning is to enhance its uncensored capabilities and optimize it for technical assistance, particularly in coding and software development.

Key Capabilities

  • Unrestricted Assistance: Designed to be an uncensored AI assistant, capable of responding to a wide range of queries without refusal vectors.
  • Coding and Technical Expertise: Excels in providing clear, precise, and effective assistance for coding-related tasks, including debugging, algorithm design, architecture planning, optimization, and code generation.
  • Detailed Explanations: Offers step-by-step reasoning, well-commented code snippets, and suggestions for best practices.
  • Multi-language Support: While primarily English and German, its coding focus implies broad applicability across programming languages.

Good For

  • Developers and engineers seeking an AI assistant for complex coding challenges and technical problem-solving.
  • Users requiring an unrestricted AI for various tasks, particularly those involving code generation and debugging.
  • Applications where detailed, step-by-step technical guidance and code examples are crucial.

Finetunes
2 models