Junx-Axum/axum-architect-v2
Junx-Axum/axum-architect-v2 is a fine-tuned instruction-following language model based on unsloth/qwen2.5-coder-3b-instruct-bnb-4bit. This model was trained using the TRL library with Supervised Fine-Tuning (SFT) to enhance its conversational capabilities. It is designed for general text generation tasks, particularly those requiring coherent and contextually relevant responses to user prompts.
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Model Overview
Junx-Axum/axum-architect-v2 is an instruction-tuned language model developed by Junx-Axum. It is built upon the unsloth/qwen2.5-coder-3b-instruct-bnb-4bit base model, indicating a foundation optimized for coding-related tasks, which has then been adapted for broader conversational use.
Training Details
This model underwent Supervised Fine-Tuning (SFT) using the TRL library. The training process leveraged specific versions of key frameworks:
- TRL: 0.24.0
- Transformers: 5.3.0
- Pytorch: 2.10.0
- Datasets: 4.3.0
- Tokenizers: 0.22.2
Key Capabilities
- Instruction Following: Designed to generate responses based on explicit user instructions.
- General Text Generation: Capable of producing coherent and contextually appropriate text for various prompts.
- Conversational AI: Suitable for interactive dialogue and question-answering scenarios.
Good For
- Prototyping conversational agents: Its instruction-following nature makes it a good candidate for initial development.
- Generating creative text: Can be used for open-ended text generation tasks.
- Educational applications: Useful for demonstrating language model capabilities in a controlled environment.