vdxap9/pas
VISIONConcurrent Unit Cost:1Model Size:5.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 8, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
vdxap9/pas is a 5.1 billion parameter language model developed by vdxap9, finetuned from unsloth/gemma-4-e2b-it-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a 32768 token context length, it is optimized for efficient performance derived from its Unsloth-accelerated finetuning process.
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Model Overview
vdxap9/pas is a 5.1 billion parameter language model, finetuned by vdxap9. It is based on the unsloth/gemma-4-e2b-it-unsloth-bnb-4bit model and features a substantial context length of 32768 tokens.
Key Characteristics
- Efficient Finetuning: This model was finetuned with Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Base Model: Derived from the
gemma-4-e2b-itarchitecture, indicating a foundation in Google's Gemma family of models. - Developer: Developed by vdxap9.
- License: Distributed under the Apache-2.0 license.
When to Consider This Model
- Performance-conscious applications: The 2x faster training with Unsloth suggests potential optimizations in the model's architecture or training methodology that could translate to efficient inference.
- Applications requiring a large context window: Its 32768 token context length makes it suitable for tasks involving extensive input or requiring a broad understanding of long documents or conversations.