lewtun/carbon-14b-sft-smoke-20260805-124457
The lewtun/carbon-14b-sft-smoke-20260805-124457 is a 14 billion parameter instruction-tuned language model, fine-tuned from HuggingFaceBio/Qwen3-14B-Instruct-Mid using the TRL framework. This model is designed for general text generation tasks, leveraging its base architecture and supervised fine-tuning to produce coherent and contextually relevant responses. It is suitable for applications requiring a robust conversational AI or text completion capabilities.
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Model Overview
lewtun/carbon-14b-sft-smoke-20260805-124457 is a 14 billion parameter language model that has been supervised fine-tuned (SFT) from the HuggingFaceBio/Qwen3-14B-Instruct-Mid base model. The fine-tuning process utilized the TRL (Transformers Reinforcement Learning) framework, specifically version 1.10.0.dev0, indicating a focus on enhancing instruction-following capabilities.
Key Capabilities
- Instruction Following: The model is fine-tuned to respond to user instructions, making it suitable for interactive applications.
- Text Generation: Capable of generating coherent and contextually appropriate text based on given prompts.
- Base Model Heritage: Benefits from the strong foundational capabilities of the
Qwen3-14B-Instruct-Midarchitecture.
Training Details
The model was trained using the SFT method, which typically involves training on a dataset of instruction-response pairs to align the model's output with human preferences and instructions. The training environment included:
- TRL: 1.10.0.dev0
- Transformers: 5.13.0.dev0
- PyTorch: 2.11.0
- Datasets: 5.0.0
- Tokenizers: 0.22.2
Good For
- General-purpose conversational AI: Responding to user queries and engaging in dialogue.
- Text completion and generation: Creating various forms of text content.
- Prototyping: Quickly setting up language model-powered applications that require instruction-tuned capabilities.