anthonym21/gemma-3-4b-it-slipstream-sft
anthonym21/gemma-3-4b-it-slipstream-sft is a 4.3 billion parameter Gemma 3-4B-IT model fine-tuned by anthonym21. This model is specifically trained on the Slipstream-TQT dataset to understand and generate messages conforming to the Slipstream inter-agent protocol. It serves as the initial supervised fine-tuning stage in a multi-stage pipeline aimed at developing AI agents capable of inter-agent communication.
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Overview
This model, gemma-3-4b-it-slipstream-sft, is a 4.3 billion parameter variant of Google's Gemma 3-4B-IT base model, developed by anthonym21. It has undergone Supervised Fine-Tuning (SFT) using LoRA (r=8, alpha=16) for one epoch. The primary objective of this fine-tuning was to teach the model the specific format and communication patterns of the Slipstream inter-agent protocol.
Key Capabilities
- Protocol Adherence: Generates text outputs that conform to the Slipstream inter-agent protocol.
- Base Model Strengths: Inherits the general language understanding and generation capabilities of the Gemma 3-4B-IT architecture.
Development Stage
This model represents the first stage (SFT) in a three-stage development pipeline. Future stages include:
- GRPO: RLHF alignment using
slipstream-gov-envfor enhanced safety and usage. - Trim: Quantization and distillation of the aligned model for optimized deployment.
Good For
- Developers working with the Slipstream inter-agent protocol.
- Research into inter-agent communication and multi-agent systems.
- As a foundational component for further alignment and optimization in the Slipstream pipeline.