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Model: arif-butt/tinyllama-peft-merged
Source: Original Platform

README.md

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+---
+language: en
+license: apache-2.0
+library_name: transformers
+tags:
+- tinyllama
+- peft
+- merged
+- lora
+- fine-tuned
+- pytorch
+- text-generation
+base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
+datasets:
+- arif-butt/arifbutt_dataset
+pipeline_tag: text-generation
+---
+
+# 🦙 TinyLlama PEFT Merged
+
+> **A fully merged, production-ready TinyLlama model fine-tuned with PEFT LoRA**
+
+---
+
+## 📌 Quick Facts
+
+| Attribute | Value |
+|-----------|-------|
+| **Model Size** | 2.2 GB |
+| **Parameters** | 1.1 Billion |
+| **Format** | PyTorch Safetensors |
+| **Precision** | FP16 |
+| **Context** | 2048 tokens |
+| **Training Framework** | PEFT + TRL |
+| **Inference** | No PEFT required |
+
+---
+
+## 🚀 Quick Start
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# One-liner to load
+tokenizer = AutoTokenizer.from_pretrained("arif-butt/tinyllama-peft-merged")
+model = AutoModelForCausalLM.from_pretrained(
+    "arif-butt/tinyllama-peft-merged",
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+# Generate
+prompt = "Q: What courses does Arif teach?\nA:"
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=100)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+
+📦 What's Inside
+tinyllama-peft-merged/
+├── model.safetensors      # 2.2 GB — merged weights
+├── config.json            # Model architecture
+├── generation_config.json # Default generation settings
+├── tokenizer.json         # Vocabulary (1.76 MB)
+├── tokenizer_config.json  # Tokenizer settings
+└── special_tokens_map.json # Special tokens
+
+No adapter files. No PEFT needed. Just load and go.
+
+
+🔧 Generation Settings
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=150,
+    temperature=0.7,
+    top_p=0.95,
+    do_sample=True,
+    repetition_penalty=1.1,
+    pad_token_id=tokenizer.eos_token_id,
+)
+
+
+💬 Prompt Format
+Q: Your question here?
+A:
+Example:
+
+  Q: What is deep learning?
+A: Deep learning is a subset of machine learning...
+
+
+Q: What is Python?
+A: Python is a high-level, interpreted programming language known for its simple, readable syntax. It supports multiple programming paradigms including object-oriented, imperative, and functional programming.
+
+Q: Explain gradient descent
+A: Gradient descent is an optimization algorithm used to minimize the loss function in machine learning models. It works by iteratively moving parameters in the direction of the negative gradient.
+
+Q: Name Arif's courses
+A: Dr. Muhammad Arif Butt teaches Python Programming, Data Structures & Algorithms, Machine Learning, and Deep Learning courses.
+
+Epoch 1: ████████████████░░░░ 0.8
+Epoch 2: ████████████████████ 0.4
+Epoch 3: ████████████████████ 0.05