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---
base_model: Qwen/Qwen2.5-Coder-3B-Instruct
datasets:
  - my-ai-stack/Stack-4.0-Dataset
license: apache-2.0
language:
  - en
library_name: transformers
pipeline_tag: text-generation
tags:
  - qwen2.5-coder
  - qwen2.5-coder-3b
  - code-generation
  - agentic-ai
  - tool-use
  - fine-tuned-llm
  - stack-4
  - stack-ai
  - sovereign-ai
  - enterprise
  - local-inference
  - 3b-parameter-model
model-index:
  - name: Stack 4.0 Omni-Nexus Merged
    results:
      - task:
          type: text-generation
          description: HellaSwag commonsense reasoning
        dataset:
          name: HellaSwag
          type: hellaswag
        metrics:
          - type: acc_norm
            value: 74.0%
      - task:
          type: text-generation
          description: ARC-Challenge reasoning
        dataset:
          name: ARC-Challenge
          type: ai2_arc
        metrics:
          - type: acc_norm
            value: 52.0%
---

<div style="background-color: #030406; padding: 60px 40px; border-radius: 40px 40px 0 0; border: 1px solid #111827; border-bottom: none; font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; color: #ffffff; text-align: center; position: relative; overflow: hidden;">

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      <div style="position: absolute; width: 100%; height: 18px; background: linear-gradient(135deg, #c084fc 0%, #db2777 100%); border-radius: 6px; top: 22px; z-index: 2; opacity: 0.7; border-bottom: 2px solid rgba(0,0,0,0.2);"></div>
      <div style="position: absolute; width: 100%; height: 18px; background: linear-gradient(135deg, #c084fc 0%, #db2777 100%); border-radius: 6px; top: 44px; z-index: 1; opacity: 0.4; border-bottom: 2px solid rgba(0,0,0,0.2);"></div>
  </div>

  <h1 style="background: linear-gradient(135deg, #ffffff 0%, #a1a1aa 100%); -webkit-background-clip: text; -webkit-text-fill-color: transparent; font-size: 3rem; letter-spacing: -1.5px; margin: 10px 0; font-weight: 800;">Stack 4.0 Omni-Nexus</h1>

  <p style="color: #db2777; font-weight: 600; letter-spacing: 3px; text-transform: uppercase; font-size: 0.85rem; margin-bottom: 30px; opacity: 0.9;">Merged · 3B Parameters · Sovereign Agentic Infrastructure</p>

  <div align="center" style="display: flex; justify-content: center; gap: 10px; flex-wrap: wrap;">
    <img src="https://img.shields.io/badge/Release-v4.0_Alpha-db2777?style=for-the-badge" alt="Version">
    <img src="https://img.shields.io/badge/Network-Global-111827?style=for-the-badge&border=db2777" alt="Network">
    <img src="https://img.shields.io/badge/Security-Sovereign-c084fc?style=for-the-badge" alt="Security">
  </div>

  <div style="height: 1px; width: 100%; background: linear-gradient(to right, transparent, #111827, #db2777, #111827, transparent); margin-top: 50px; opacity: 0.5;"></div>
</div>

---

# Stack 4.0 Omni-Nexus — Merged

**Model ID:** `my-ai-stack/Stack-4.0-Qwen-3B-Merged`

A 3-billion parameter instruction-tuned coding model, fully merged from Qwen2.5-Coder-3B-Instruct with 55,000 agentic tool-use conversations baked in. This is the standalone version — no adapter needed, runs directly on any compatible hardware.

## Performance Benchmarks

| Benchmark | Score | Notes |
|-----------|-------|-------|
| HellaSwag (acc_norm) | **74.0%** | 50-sample eval |
| ARC-Challenge (acc_norm) | **52.0%** | 50-sample eval |
| Internal coding sample | **10/10** | All valid Python produced |

## Key Metrics

| Metric | Value |
|--------|-------|
| Parameters | **3B** |
| Training loss (final) | **0.1411** |
| Training steps | 1,000 |
| Hardware | GCP Tesla V100 16GB |
| Training time | ~10 hours |

## Why Merged?

The merged version ships the full model in a single file — no LoRA adapters, no base model dependency. Deploy anywhere that supports Hugging Face Transformers.

## Usage

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

MODEL = "my-ai-stack/Stack-4.0-Qwen-3B-Merged"

tokenizer = AutoTokenizer.from_pretrained(MODEL, trust_remote_code=True)
tokenizer.pad_token = tokenizer.eos_token

model = AutoModelForCausalLM.from_pretrained(
    MODEL, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True
)
model.eval()

messages = [{"role": "user", "content": "Write a quicksort in Python"}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)

with torch.no_grad():
    out = model.generate(**inputs, max_new_tokens=512, temperature=0.7)

print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
```

## Training Details

| Parameter | Value |
|-----------|-------|
| Method | QLoRA → Merged |
| LoRA rank | 16 |
| Trainable params | 7.3M / 3.1B (0.24%) |
| Batch size | 1 |
| Grad accumulation | 16 |
| Max length | 512 |
| Learning rate | 2e-4 |
| Optimizer | AdamW (bf16) |
| Hardware | GCP V100 16GB |

## Limitations

- **3B model** — smaller than 7B models; less capable on complex multi-step reasoning
- **English-optimized** — other language performance may vary
- **Tool execution** — tool calls are generated but actual execution requires an agent loop in your application

## See Also

- [LoRA Adapter version](https://huggingface.co/my-ai-stack/Stack-4.0-Qwen-3B-Agentic) — smaller, needs base model
- [Training dataset](https://huggingface.co/my-ai-stack/Stack-4.0-Dataset)
- [Stack 3.0 (7B)](https://huggingface.co/my-ai-stack/Stack-3.0-Omni-Nexus)

## Citation

```bibtex
@misc{stack-4-merged-2026,
  title={Stack 4.0 Omni-Nexus — Merged},
  author={Stack AI Team},
  year={2026},
  url={https://huggingface.co/my-ai-stack/Stack-4.0-Qwen-3B-Merged}
}
```