Update README.md

README.md

@@ -1,62 +1,228 @@
 ---
-base_model:
-- microsoft/NextCoder-7B
-- nvidia/OpenCodeReasoning-Nemotron-7B
-- Qwen/Qwen2.5-7B
-- Qwen/Qwen2.5-Coder-7B
+license: other
 library_name: transformers
+base_model:
+  - microsoft/NextCoder-7B
+  - nvidia/OpenCodeReasoning-Nemotron-7B
+  - Qwen/Qwen2.5-7B
+  - Qwen/Qwen2.5-Coder-7B
 tags:
-- mergekit
-- merge
+  - qwen2
+  - mergekit
+  - merge
+  - conversational
+  - text-generation-inference
+  - code
+  - reasoning
+  - withinusai
+language:
+  - en
 datasets:
-- bigcode/commitpackft
-- microsoft/NextCoderDataset-Conversational
-- bigcode/starcoderdata
-- nvidia/OpenCodeReasoning
+  - bigcode/commitpackft
+  - microsoft/NextCoderDataset-Conversational
+  - bigcode/starcoderdata
+  - nvidia/OpenCodeReasoning
+pipeline_tag: text-generation
 ---
+
 # Next_Nemotron_Reasoning_Coder-7B
 
-This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+**Next_Nemotron_Reasoning_Coder-7B** is a merged 7B-class language model release from **WithIn Us AI**, designed for coding, conversational prompting, and reasoning-oriented text generation.
+
+This repository is distributed as a standard **Transformers** checkpoint in **Safetensors** format and is positioned as a merge-based model that blends coding and reasoning-oriented upstream model traits.
+
+## Model Summary
+
+This model is intended for:
+
+- code generation
+- code explanation
+- conversational assistant workflows
+- reasoning-oriented prompting
+- implementation planning
+- developer support tasks
+- general text generation experiments
+
+The current repository metadata and README indicate that this model is a **merge model** built with **mergekit**.
+
+## Base Model Lineage
+
+The current README metadata lists the following upstream model references:
+
+- `microsoft/NextCoder-7B`
+- `nvidia/OpenCodeReasoning-Nemotron-7B`
+- `Qwen/Qwen2.5-7B`
+- `Qwen/Qwen2.5-Coder-7B`
+
+These names are preserved here as listed in the repository metadata.
 
 ## Merge Details
-### Merge Method
-
-This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
-
-### Models Merged
-
-The following models were included in the merge:
-* nvidia-OpenCodeReasoning-Nemotron-7B
-* microsoft-NextCoder-7B
-
-### Configuration
-
-The following YAML configuration was used to produce this model:
-
-```yaml
-base_model: C:/Users/GSS1147/Desktop/nvidia-OpenCodeReasoning-Nemotron-7B
-dtype: float16
-merge_method: slerp
-parameters:
-  t:
-  - filter: embed_tokens
-    value: 0.0
-  - filter: self_attn
-    value: 0.5
-  - filter: mlp
-    value: 0.5
-  - filter: lm_head
-    value: 1.0
-  - value: 0.5
-slices:
-- sources:
-  - layer_range:
-    - 0
-    - 28
-    model: C:/Users/GSS1147/Desktop/nvidia-OpenCodeReasoning-Nemotron-7B
-  - layer_range:
-    - 0
-    - 28
-    model: C:/Users/GSS1147/Desktop/microsoft-NextCoder-7B
-
-```
+
+According to the current README:
+
+- this model is a **merge of pre-trained language models**
+- it was created using **mergekit**
+- the **SLERP** merge method was used
+- the “Models Merged” section explicitly lists:
+  - `nvidia-OpenCodeReasoning-Nemotron-7B`
+  - `microsoft-NextCoder-7B`
+
+The repository also includes a visible `mergekit_config.yml`, which supports the merge-based packaging of the release.
+
+## Training Data / Dataset Lineage
+
+The current repository metadata lists the following datasets:
+
+- `bigcode/commitpackft`
+- `microsoft/NextCoderDataset-Conversational`
+- `bigcode/starcoderdata`
+- `nvidia/OpenCodeReasoning`
+
+These datasets suggest a mix of:
+
+- code-focused training data
+- conversational coding supervision
+- general programming corpus material
+- reasoning-oriented coding data
+
+## Intended Use
+
+Recommended use cases include:
+
+- coding assistant experiments
+- code drafting and rewriting
+- explaining code and technical concepts
+- debugging support
+- reasoning-style prompt workflows
+- local or hosted developer-assistant inference
+- structured implementation planning
+
+## Suggested Use Cases
+
+This model can be useful for:
+
+- generating utility functions and scripts
+- explaining programming concepts
+- proposing debugging steps
+- creating technical plans
+- answering developer questions
+- assisting with code-oriented chat workflows
+
+## Out-of-Scope Use
+
+This model should not be relied on for:
+
+- legal advice
+- medical advice
+- financial advice
+- safety-critical automation
+- autonomous production engineering without review
+- security-critical code without expert validation
+
+All generated code should be reviewed, tested, and validated before real-world deployment.
+
+## Repository Contents
+
+The repository currently includes standard Hugging Face model assets such as:
+
+- `README.md`
+- `added_tokens.json`
+- `config.json`
+- `mergekit_config.yml`
+- `merges.txt`
+- `model-00001-of-00004.safetensors`
+- `model-00002-of-00004.safetensors`
+- `model-00003-of-00004.safetensors`
+- `model.safetensors.index.json`
+- `special_tokens_map.json`
+- `tokenizer.json`
+- `tokenizer_config.json`
+
+## Prompting Guidance
+
+This model will usually work best with prompts that are:
+
+- direct
+- scoped to a clear task
+- explicit about language or framework
+- specific about whether code, explanation, or both are wanted
+- structured when reasoning steps are needed
+
+### Example prompt styles
+
+**Code generation**
+> Write a Python function that parses a JSON file, validates required keys, and returns cleaned records.
+
+**Debugging**
+> Explain why this code raises a KeyError and provide a safer corrected version.
+
+**Implementation planning**
+> Create a step-by-step plan for building a FastAPI service with authentication, logging, and tests.
+
+**Reasoning-oriented coding**
+> Compare two approaches for implementing caching in a Python API and recommend one.
+
+## Strengths
+
+This model may be especially useful for:
+
+- blended coding + reasoning workflows
+- chat-style developer assistance
+- merge-model experimentation
+- structured software-task prompting
+- moderate-scale local or hosted inference
+- practical code-oriented text generation
+
+## Limitations
+
+Like other merged 7B-class language models, this model may:
+
+- hallucinate APIs or technical details
+- generate incomplete or incorrect code
+- produce insecure implementations
+- make reasoning mistakes on long or complex tasks
+- require prompt iteration for best results
+- need human validation before real-world use
+
+## Attribution
+
+**WithIn Us AI** is the publisher of this merged model release.
+
+Credit for upstream assets remains with their original creators. The repository metadata and README specifically reference:
+
+- `microsoft/NextCoder-7B`
+- `nvidia/OpenCodeReasoning-Nemotron-7B`
+- `Qwen/Qwen2.5-7B`
+- `Qwen/Qwen2.5-Coder-7B`
+
+and the datasets:
+
+- `bigcode/commitpackft`
+- `microsoft/NextCoderDataset-Conversational`
+- `bigcode/starcoderdata`
+- `nvidia/OpenCodeReasoning`
+
+## License
+
+This draft uses:
+
+- `license: other`
+
+If you maintain this repo, replace this with the exact license terms you want displayed and make sure they align with any upstream obligations from the referenced source models and datasets.
+
+## Acknowledgments
+
+Thanks to:
+
+- **WithIn Us AI**
+- **Microsoft**
+- **NVIDIA**
+- **Qwen**
+- **BigCode**
+- the **mergekit** ecosystem
+- the Hugging Face platform
+- the broader open-source LLM community
+
+## Disclaimer
+
+This model may produce inaccurate, insecure, biased, incomplete, or misleading outputs. All important generations, especially code and technical guidance, should be reviewed and tested before real-world use.