charcoalfilter/textpulse-v3-qwen3-4b
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Apr 1, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The charcoalfilter/textpulse-v3-qwen3-4b is a 4 billion parameter Qwen3-based causal language model developed by charcoalfilter. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its efficient training methodology for practical applications.
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Model Overview
The charcoalfilter/textpulse-v3-qwen3-4b is a 4 billion parameter language model based on the Qwen3 architecture. Developed by charcoalfilter, this model was fine-tuned using a combination of Unsloth and Huggingface's TRL library.
Key Characteristics
- Architecture: Qwen3-based, a powerful causal language model family.
- Parameter Count: 4 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Utilizes Unsloth for significantly faster fine-tuning, reportedly achieving 2x speed improvements during its training process.
- License: Released under the Apache-2.0 license, allowing for broad use and distribution.
Good For
- General Language Tasks: Suitable for a wide range of natural language processing applications.
- Efficient Deployment: Its moderate size and efficient training suggest it can be a good candidate for applications where faster iteration or deployment on less powerful hardware is desired.
- Research and Development: Provides a base for further experimentation and fine-tuning, especially for those interested in Unsloth's training methodologies.