Update README.md

README.md

@@ -1,12 +1,179 @@
 ---
-datasets:
-- gss1147/Python_GOD_Coder_25k
-- deepmind/code_contests
-- djaym7/wiki_dialog
+license: other
+library_name: transformers
 base_model:
-- gss1147/flanT5-MoE-7X0.1B
+  - gss1147/flanT5-MoE-7X0.1B
 tags:
-- Google
-- PythonGODCoder25x
+  - t5
+  - Google
+  - PythonGODCoder25x
+  - code
+  - coding-assistant
+  - text2text-generation
+  - instruction-following
+  - withinusai
+language:
+  - en
+datasets:
+  - gss1147/Python_GOD_Coder_25k
+  - deepmind/code_contests
+  - djaym7/wiki_dialog
+pipeline_tag: text2text-generation
 ---
----
+
+# flanT5-MoE-7X0.1B-PythonGOD-25k
+
+**flanT5-MoE-7X0.1B-PythonGOD-25k** is a compact text-to-text generation model from **WithIn Us AI**, built on top of **`gss1147/flanT5-MoE-7X0.1B`** and positioned for coding-oriented instruction following, technical prompting, and lightweight structured generation.
+
+This model is best suited for users who want a small T5-style checkpoint for code-help tasks, prompt-to-output transformations, implementation planning, and concise assistant workflows.
+
+## Model Summary
+
+This model is designed for:
+
+- code-oriented instruction following
+- Python-focused prompt tasks
+- structured text-to-text generation
+- compact implementation assistance
+- lightweight coding workflows
+- technical transformation tasks
+
+Because this model follows the **T5 / Flan-T5 text-to-text format**, it generally performs best when prompts are written as direct tasks rather than as vague open-ended chat.
+
+## Base Model
+
+This model is based on:
+
+- **`gss1147/flanT5-MoE-7X0.1B`**
+
+## Training Data
+
+The current repository metadata lists the following datasets in the model lineage:
+
+- **`gss1147/Python_GOD_Coder_25k`**
+- **`deepmind/code_contests`**
+- **`djaym7/wiki_dialog`**
+
+These sources suggest a blend of coding-focused supervision, contest-style programming content, and conversational or dialogue-style instruction material.
+
+## Intended Use
+
+This model is intended for:
+
+- code generation prompts
+- coding assistant prototypes
+- instruction-based code rewriting
+- implementation planning
+- compact local or hosted inference
+- structured development-task responses
+
+## Recommended Use Cases
+
+This model can be used for:
+
+- generating short Python functions
+- rewriting code into cleaner or more readable form
+- explaining snippets of code
+- producing small implementation plans
+- answering coding prompts in a concise format
+- transforming developer requests into structured outputs
+
+## Out-of-Scope Use
+
+This model should not be relied on for:
+
+- legal advice
+- medical advice
+- financial advice
+- autonomous production code deployment
+- security-critical code generation without review
+- high-stakes decisions without human verification
+
+All generated code should be reviewed, tested, and validated before use.
+
+## Model Format
+
+This repository currently includes standard Hugging Face model artifacts such as:
+
+- `config.json`
+- `generation_config.json`
+- `model.safetensors`
+- `tokenizer.json`
+- `tokenizer_config.json`
+
+The model is hosted as a **Transformers** checkpoint and is suitable for standard `transformers` inference workflows.  [oai_citation:1‡Hugging Face](https://huggingface.co/WithinUsAI/flanT5-MoE-7X0.1B-PythonGOD-25k/tree/main)
+
+## Prompting Guidance
+
+This model works best with clear, direct instructions.
+
+### Example prompt styles
+
+**Code generation**
+> Write a Python function that loads a JSON file, removes duplicate records by email, and saves the cleaned result.
+
+**Explanation**
+> Explain what this Python function does and identify any bugs or edge cases.
+
+**Refactoring**
+> Refactor this code for readability and add error handling.
+
+**Planning**
+> Create a step-by-step implementation plan for a simple Flask API with login and logging.
+
+## Strengths
+
+This model may be especially useful for:
+
+- compact inference footprints
+- text-to-text coding prompts
+- structured responses
+- lightweight implementation help
+- fast experimentation
+- small-model workflows
+
+## Limitations
+
+Like other compact language models, this model may:
+
+- hallucinate APIs or code details
+- generate incomplete or incorrect code
+- struggle with long or deeply complex tasks
+- lose precision on multi-step reasoning
+- require prompt iteration for best results
+- underperform larger models on advanced debugging and architecture work
+
+Human review is strongly recommended.
+
+## Attribution
+
+**WithIn Us AI** is the creator of this release, including the model packaging, presentation, and project identity.
+
+Credit for upstream assets remains with their original creators, including:
+
+- the creators of **`gss1147/flanT5-MoE-7X0.1B`**
+- the creators of **`gss1147/Python_GOD_Coder_25k`**
+- **DeepMind** for **`deepmind/code_contests`**
+- the creator of **`djaym7/wiki_dialog`**
+
+## License
+
+This model card uses:
+
+- `license: other`
+
+Use the repository `LICENSE` file or your project-specific license text to define exact redistribution and usage terms.
+
+## Acknowledgments
+
+Thanks to:
+
+- **WithIn Us AI**
+- the upstream creators of the base model
+- the dataset creators listed above
+- the Hugging Face ecosystem
+- the open-source ML community
+
+## Disclaimer
+
+This model may produce inaccurate, incomplete, insecure, or biased outputs. All generations, especially code and technical instructions, should be reviewed and tested before real-world use.