Create README.md

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-14B
+tags:
+  - text-generation
+  - conversational
+  - fine-tuned
+  - qwen3
+  - nova
+  - novamind
+  - lora
+  - qlora
+  - unsloth
+language:
+  - en
+pipeline_tag: text-generation
+library_name: transformers
+model_type: qwen3
+inference: true
+datasets:
+  - custom
+metrics:
+  - accuracy
+widget:
+  - text: "Who are you?"
+    example_title: "Identity"
+  - text: "What is a REST API?"
+    example_title: "Technical Question"
+  - text: "Write a Python function to reverse a string"
+    example_title: "Code Generation"
+---
+
+# 🧠 Nova2-14B
+
+<p align="center">
+  <img src="https://img.shields.io/badge/Base%20Model-Qwen3--14B-blue?style=flat-square" />
+  <img src="https://img.shields.io/badge/Fine--tuned%20with-Unsloth%20%2B%20QLoRA-green?style=flat-square" />
+  <img src="https://img.shields.io/badge/License-Apache%202.0-orange?style=flat-square" />
+  <img src="https://img.shields.io/badge/Language-English-red?style=flat-square" />
+  <img src="https://img.shields.io/badge/Parameters-14B-purple?style=flat-square" />
+</p>
+
+**Nova2-14B** is a fine-tuned large language model built on top of [Qwen/Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B).
+It is the core model powering **NovaMind** — an AI chat application developed by **Frederick Sundeep Mallela**.
+
+Nova2-14B is a **fully standalone merged model** — the LoRA adapter has been permanently baked into the base weights,
+requiring no adapter dependency at inference time.
+
+---
+
+## 🚀 Model Description
+
+| Property | Value |
+|---|---|
+| **Model Name** | Nova2-14B |
+| **Developer** | Frederick Sundeep Mallela |
+| **Base Model** | Qwen/Qwen3-14B |
+| **Fine-tuning Method** | QLoRA (Quantized Low-Rank Adaptation) |
+| **Fine-tuning Framework** | Unsloth + TRL |
+| **Model Type** | Causal Language Model |
+| **Parameters** | ~14.7 Billion |
+| **Context Length** | 2048 tokens (base supports up to 40K) |
+| **Language** | English |
+| **License** | Apache 2.0 |
+| **Merge Status** | ✅ Fully merged — standalone base model |
+
+---
+
+## 💡 What Makes Nova2-14B Different
+
+Nova2-14B retains **all of Qwen3-14B's capabilities** — coding, reasoning, math, multilingual support —
+while adding a custom persona and identity through supervised fine-tuning:
+
+- Responds as **Nova**, an AI assistant created by Frederick
+- Consistent identity across all conversation styles
+- Trained to never reveal underlying architecture details
+- Optimized for use in the **NovaMind** chat application
+
+---
+
+## 🛠️ How to Use
+
+### Basic Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "FrederickSundeep/nova2-14b"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+model.eval()
+
+messages = [
+    {"role": "system", "content": "You are Nova, an AI assistant created by Frederick."},
+    {"role": "user",   "content": "Who are you?"},
+]
+
+inputs = tokenizer.apply_chat_template(
+    messages,
+    tokenize=True,
+    add_generation_prompt=True,
+    enable_thinking=False,
+    return_tensors="pt",
+).to(model.device)
+
+with torch.no_grad():
+    outputs = model.generate(
+        input_ids=inputs,
+        max_new_tokens=512,
+        temperature=0.7,
+        top_p=0.8,
+        top_k=20,
+        do_sample=True,
+        repetition_penalty=1.05,
+        pad_token_id=tokenizer.eos_token_id,
+    )
+
+response = tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True)
+print(response)
+```
+
+### With 4-bit Quantization (Low VRAM)
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+import torch
+
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_compute_dtype=torch.float16,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+)
+
+model_id = "FrederickSundeep/nova2-14b"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    quantization_config=bnb_config,
+    device_map="auto",
+)
+```
+
+### Recommended Generation Parameters
+
+```python
+# For conversational / chat use
+generation_config = {
+    "temperature": 0.7,
+    "top_p": 0.8,
+    "top_k": 20,
+    "repetition_penalty": 1.05,
+    "do_sample": True,
+    "max_new_tokens": 1024,
+}
+
+# For coding / precise tasks
+generation_config_precise = {
+    "temperature": 0.3,
+    "top_p": 0.9,
+    "do_sample": True,
+    "max_new_tokens": 2048,
+}
+```
+
+---
+
+## 🏋️ Training Details
+
+### Fine-tuning Setup
+
+| Setting | Value |
+|---|---|
+| **Base Model** | unsloth/Qwen3-14B-bnb-4bit |
+| **Method** | Supervised Fine-Tuning (SFT) with QLoRA |
+| **LoRA Rank** | 16 |
+| **LoRA Alpha** | 16 |
+| **Target Modules** | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
+| **Batch Size** | 2 (effective 8 with gradient accumulation) |
+| **Gradient Accumulation** | 4 steps |
+| **Learning Rate** | 2e-4 |
+| **Epochs** | 3 |
+| **Optimizer** | AdamW 8-bit |
+| **LR Scheduler** | Linear |
+| **Max Sequence Length** | 2048 |
+| **Training Hardware** | NVIDIA Tesla T4 (16GB) via Google Colab |
+| **Training Framework** | Unsloth + TRL SFTTrainer |
+| **Thinking Mode** | Disabled (enable_thinking=False) |
+
+### Dataset
+
+Custom curated dataset of conversational examples covering:
+- **Identity & persona** — Nova's name, creator, what it is and isn't
+- **Technical knowledge** — coding, system design, AI/ML concepts
+- **Personality & tone** — concise, direct, technically precise responses
+- **Edge cases** — handling questions about underlying architecture
+
+---
+
+## ⚙️ Hardware Requirements
+
+| Setup | VRAM | Notes |
+|---|---|---|
+| Full fp16 | ~28 GB | A100 80GB or 2x A40 |
+| 8-bit quantized | ~15 GB | Single A100 40GB or RTX 3090 |
+| 4-bit quantized | ~9 GB | Single RTX 3080/3090/4090 or T4 |
+| CPU only | 32 GB RAM | Very slow — not recommended |
+
+---
+
+## 📊 Capabilities
+
+Nova2-14B inherits all Qwen3-14B capabilities:
+
+- ✅ **Code generation** — Python, JavaScript, TypeScript, Java, C++, SQL, and more
+- ✅ **Reasoning** — step-by-step logical problem solving
+- ✅ **Math** — arithmetic to advanced mathematics
+- ✅ **Instruction following** — precise task execution
+- ✅ **Multilingual** — 100+ languages (from base model)
+- ✅ **Long context** — supports up to 40K tokens (base architecture)
+- ✅ **Tool use** — function calling compatible
+- ✅ **System prompt** — fully supports custom system prompts
+
+---
+
+## 🔒 Intended Use
+
+**Intended for:**
+- Powering the NovaMind AI chat application
+- General-purpose AI assistant tasks
+- Code generation and debugging
+- Technical question answering
+- Further fine-tuning as a base model
+
+**Not intended for:**
+- Harmful, unethical, or illegal content generation
+- Medical or legal advice without human oversight
+- High-stakes autonomous decision making
+
+---
+
+## ⚠️ Limitations
+
+- Fine-tuned on a relatively small custom dataset — may occasionally revert to base Qwen3 behavior in edge cases
+- Not evaluated on standard benchmarks post fine-tuning
+- Thinking mode disabled during fine-tuning — re-enable via `enable_thinking=True` in chat template if needed
+- Context limited to 2048 tokens in fine-tuned configuration (base supports 40K)
+
+---
+
+## 🔗 Related
+
+- **NovaMind App:** AI chat application powered by this model
+- **Base Model:** [Qwen/Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B)
+- **Fine-tuning Framework:** [Unsloth](https://github.com/unslothai/unsloth)
+- **Developer:** Frederick Sundeep Mallela
+
+---
+
+## 📄 License
+
+This model is released under the **Apache 2.0 License**, inheriting the license of the base model Qwen3-14B.
+
+See [LICENSE](https://www.apache.org/licenses/LICENSE-2.0) for full details.
+
+---
+
+## 📝 Citation
+
+If you use Nova2-14B in your research or application, please cite:
+
+```bibtex
+@misc{nova2-14b-2025,
+  author       = {Frederick Sundeep Mallela},
+  title        = {Nova2-14B: A Fine-tuned Conversational AI Assistant},
+  year         = {2025},
+  publisher    = {HuggingFace},
+  howpublished = {\url{https://huggingface.co/FrederickSundeep/nova2-14b}},
+  note         = {Fine-tuned from Qwen/Qwen3-14B using QLoRA and Unsloth}
+}
+```