| --- |
| model_name: GPT-OSS AgentBoi |
| base_model: unsloth/gpt-oss-20b-unsloth-bnb-4bit |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - gpt-oss |
| - agent |
| - tool-calling |
| - react |
| - lora |
| - unsloth |
| - trl |
| - reasoning |
| - harmony |
| - text-generation |
| pipeline_tag: text-generation |
| library_name: transformers |
| --- |
| |
| # GPT-OSS AgentBoi |
|
|
| A parameter-efficient fine-tuning of GPT-OSS-20B focused on improving agentic reasoning, structured tool use, and ReAct-style instruction following. |
|
|
| This model was fine-tuned using LoRA adapters on the ReAct subset of Agent-FLAN with the goal of making GPT-OSS more reliable at multi-step reasoning, tool selection, action-observation workflows, and structured agent behavior. |
|
|
| ## Overview |
|
|
| Large language models are often strong conversationalists but can struggle with: |
|
|
| - Multi-step planning |
| - Tool selection and invocation |
| - ReAct-style reasoning workflows |
| - Structured action generation |
| - Separating reasoning from final responses |
|
|
| GPT-OSS AgentBoi adapts GPT-OSS-20B toward these agent-oriented tasks while remaining trainable on consumer hardware through parameter-efficient fine-tuning. |
|
|
| ## Model Details |
|
|
| | Item | Value | |
| |--------|--------| |
| | Model Name | GPT-OSS AgentBoi | |
| | Author | shiv207 | |
| | Base Model | unsloth/gpt-oss-20b-unsloth-bnb-4bit | |
| | Training Method | LoRA | |
| | Framework | Unsloth | |
| | Dataset | Agent-FLAN (ReAct subset) | |
| | Primary Task | Agentic Tool Use | |
| | Language | English | |
| | License | Apache 2.0 | |
|
|
| ## Training Data |
|
|
| The model was fine-tuned using examples from the Agent-FLAN dataset, specifically the ReAct-style instruction trajectories. |
|
|
| These examples teach the model to: |
|
|
| - Break complex tasks into intermediate steps |
| - Decide when tool usage is appropriate |
| - Generate structured actions |
| - Follow action-observation loops |
| - Produce concise final responses |
|
|
| ## Training Setup |
|
|
| Training was performed using: |
|
|
| - GPT-OSS-20B |
| - Unsloth |
| - TRL |
| - LoRA adapters |
| - Google Colab Tesla T4 GPU |
|
|
| The objective was to improve agentic behavior while keeping training accessible on limited hardware. |
|
|
| ## Intended Use |
|
|
| This model is intended for: |
|
|
| - AI agents |
| - Tool-calling systems |
| - Research assistants |
| - Retrieval-augmented generation workflows |
| - Multi-step planning tasks |
| - Agentic reasoning experiments |
|
|
| Potential applications include: |
|
|
| - Search agents |
| - Knowledge retrieval systems |
| - Function-calling assistants |
| - Research copilots |
| - Workflow automation agents |
|
|
| ## Example |
|
|
| ### User |
|
|
| ```text |
| Search for the latest SpaceX launch and summarize it. |
| ``` |
|
|
| ### Expected Agent Behavior |
|
|
| 1. Analyze the request. |
| 2. Determine that external information is required. |
| 3. Generate a structured search action. |
| 4. Process retrieved information. |
| 5. Produce a concise final answer. |
|
|
| The fine-tuning objective is to increase consistency in these workflows compared to the base model. |
|
|
| ## Loading the Model |
|
|
| ```python |
| from unsloth import FastLanguageModel |
| |
| model, tokenizer = FastLanguageModel.from_pretrained( |
| "shiv207/gpt_oss_AGENTBOI" |
| ) |
| ``` |
|
|
| ## Limitations |
|
|
| - Evaluated primarily through qualitative testing. |
| - No formal benchmark suite was used. |
| - Training utilized only a subset of Agent-FLAN. |
| - Performance may vary on unseen tool schemas. |
| - Not optimized for general-purpose instruction tuning beyond agent-oriented tasks. |
|
|
| ## Acknowledgments |
|
|
| This project builds upon the work of: |
|
|
| - OpenAI for GPT-OSS and the Harmony conversation format. |
| - Unsloth for efficient GPT-OSS fine-tuning support. |
| - InternLM for the Agent-FLAN dataset. |
|
|
| ## Repository |
|
|
| Source code and training notebook: |
|
|
| GitHub: https://github.com/shiv207 |
|
|
| ## Author |
|
|
| **shiv207** |
|
|
| If you find this project useful, feel free to open issues, share feedback, or build on top of it. |
