flanT5-MoE-7X0.1B-PythonGOD-AgenticAI
flanT5-MoE-7X0.1B-PythonGOD-AgenticAI is a text-to-text generation model from WithIn Us AI, built as a fine-tuned derivative of gss1147/flanT5-MoE-7X0.1B-PythonGOD-25k and further trained for coding-oriented and agentic-style instruction following.
This model is intended for lightweight local or hosted inference workflows where a compact instruction-tuned model is useful for structured responses, code help, implementation planning, and tool-oriented prompting.
Model Summary
This model is designed for:
- code-oriented instruction following
- lightweight agentic prompting
- implementation planning
- coding assistance
- structured text generation
- compact text-to-text tasks
Because this model is built in the Flan-T5 / T5 text-to-text style, it is best prompted with clear task instructions and expected outputs rather than open-ended chat-only prompting.
Base Model
This model is a fine-tuned version of:
gss1147/flanT5-MoE-7X0.1B-PythonGOD-25k
Training Data
The current repository metadata identifies the following datasets in the model lineage:
gss1147/Python_GOD_Coder_25kWithinUsAI/Got_Agentic_AI_5k
This model card reflects the currently visible metadata on the Hugging Face repository.
Intended Use
Recommended use cases include:
- Python and general coding help
- instruction-based code generation
- implementation planning
- structured assistant responses
- compact agentic AI experiments
- transformation tasks such as rewriting, summarizing, and reformatting technical text
Suggested Use Cases
This model can be useful for:
- generating small code snippets
- rewriting code instructions into actionable steps
- producing structured implementation plans
- answering coding questions in text-to-text format
- converting prompts into concise development outputs
- supporting lightweight agent-style task decomposition
Out-of-Scope Use
This model should not be relied on for:
- legal advice
- medical advice
- financial advice
- fully autonomous high-stakes decision making
- security-critical code generation without human review
- production deployment without evaluation and testing
All generated code and technical guidance should be reviewed by a human before real-world use.
Architecture and Format
This repository is currently tagged as:
The model is distributed as a standard Hugging Face Transformers checkpoint with files including:
config.jsongeneration_config.jsonmodel.safetensorstokenizer.jsontokenizer_config.jsontraining_args.bin
Prompting Guidance
This model is best used with direct instruction prompts. Clear task framing tends to work better than vague prompts.
Example prompt styles
Code generation
Write a Python function that loads a JSON file, validates required keys, and returns cleaned records.
Implementation planning
Create a step-by-step implementation plan for building a Flask API with authentication and logging.
Debugging help
Explain why this Python function fails on missing keys and rewrite it with safe error handling.
Agentic task framing
Break this software request into ordered implementation steps, dependencies, and testing tasks.
Strengths
This model may be especially useful for:
- compact inference footprints
- instruction-following behavior
- coding-oriented prompt tasks
- text transformation workflows
- lightweight task decomposition
- structured output generation
Limitations
Like other compact language models, this model may:
- hallucinate APIs or implementation details
- produce incomplete or overly simplified code
- lose accuracy on long or complex prompts
- make reasoning mistakes on deep multi-step tasks
- require prompt iteration for best results
- underperform larger models on advanced planning or debugging
Human review is strongly recommended.
Training and Attribution Notes
WithIn Us AI is the creator of this model release and its packaging, naming, and fine-tuning presentation.
This card does not claim ownership over third-party or upstream assets unless explicitly stated by their original creators. Credit remains with the creators of the upstream base model and any datasets used in training.
License
This model card uses:
Use the repository LICENSE file or project-specific license text to define the exact redistribution and usage terms.
Acknowledgments
Thanks to:
- WithIn Us AI
- the creators of
gss1147/flanT5-MoE-7X0.1B-PythonGOD-25k
- the dataset creators behind
gss1147/Python_GOD_Coder_25k and WithinUsAI/Got_Agentic_AI_5k
- the Hugging Face ecosystem
- the broader open-source ML community
Disclaimer
This model may produce inaccurate, incomplete, insecure, or biased outputs. All generations, especially code and implementation guidance, should be reviewed and tested before real-world use.
