--- base_model: Qwen/Qwen3-VL-8B language: en library_name: mlx license: apache-2.0 pipeline_tag: text-generation tags: - mlx - apple-silicon - qlora - gftd - qwen3-vl - knowledge-distillation - whitehead - process-philosophy - organism - prehension --- # Model Card for Model ID ## Model Details ### Model Description # gftd/whitehead-260213 **Whitehead Process Philosophy Model** - A model informed by Whitehead's process philosophy: process over substance, actual occasions, creative advance, prehension, eternal objects, and the philosophy of organism. ## Philosophy: Alfred North Whitehead Whitehead's process philosophy holds that reality consists not of static substances but of processes of becoming. Every event is an 'actual occasion' that prehends (feels) its environment and achieves a novel synthesis. This model applies Whitehead's thinking to computation: services are organisms, messages are prehensions, architectures are societies of interconnected processes, and good design is creative advance toward organic unity. ## Training Details - **Framework**: Apple MLX (mlx-lm QLoRA) - **Base Model**: Qwen/Qwen3-VL-8B - **Teacher**: Claude Opus 4.6 (via OpenRouter) - **LoRA Config**: rank=64, alpha=128, layers=16, bits=4 - **Dataset**: 100 samples across 6 categories ## Capabilities - Go/Rust/Svelte/Python code generation - MCP tool selection and operation (93+ tools) - 8-step reasoning chains - Web browser interaction - Dapr patterns (Actors, Workflows, State, PubSub) - GFTD Performers API operations ## Usage (MLX) ```python from mlx_lm import load, generate model, tokenizer = load("gftd/whitehead-260213") response = generate(model, tokenizer, prompt="Write a Go HTTP handler", max_tokens=512) ``` ## License Apache 2.0 - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** en - **License:** apache-2.0 - **Finetuned from model [optional]:** Qwen/Qwen3-VL-8B ### Model Sources [optional] - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses ### Direct Use [More Information Needed] ### Downstream Use [optional] [More Information Needed] ### Out-of-Scope Use [More Information Needed] ## Bias, Risks, and Limitations [More Information Needed] ### Recommendations Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data [More Information Needed] ### Training Procedure #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] #### Speeds, Sizes, Times [optional] [More Information Needed] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data [More Information Needed] #### Factors [More Information Needed] #### Metrics [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] [More Information Needed] ## Environmental Impact Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]