PetarKal/Qwen3-4B-Base-ascii-art-v6-phase2c-generation-lr3e6
PetarKal/Qwen3-4B-Base-ascii-art-v6-phase2c-generation-lr3e6 is a 4 billion parameter language model, fine-tuned from PetarKal/Qwen3-4B-Base-ascii-art-v6-phase1-understanding. This model was trained using the TRL framework with SFT, building upon its predecessor's capabilities. It is designed for text generation tasks, leveraging a 32768 token context length.
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Model Overview
This model, PetarKal/Qwen3-4B-Base-ascii-art-v6-phase2c-generation-lr3e6, is a 4 billion parameter language model. It represents a fine-tuned iteration of the PetarKal/Qwen3-4B-Base-ascii-art-v6-phase1-understanding model, indicating a progression in its training and specialization.
Key Capabilities
- Text Generation: The model is primarily designed for generating text, as suggested by its
phase2c-generationdesignation. - Fine-tuned with TRL: Training was conducted using the TRL (Transformers Reinforcement Learning) framework, specifically employing Supervised Fine-Tuning (SFT).
- Extended Context Window: It supports a substantial context length of 32768 tokens, allowing for processing and generating longer sequences of text.
Training Details
The model's training procedure involved SFT, building upon a previous phase of development. The process utilized specific versions of key frameworks:
- TRL: 0.29.1
- Transformers: 5.5.0
- Pytorch: 2.10.0
- Datasets: 4.8.4
- Tokenizers: 0.22.2
Good For
- Developers looking for a Qwen3-based model fine-tuned for generation tasks.
- Experimentation with models trained using the TRL framework and SFT methods.