README.md

metadata

title: thoshan_Flash
emoji: 🐨
colorFrom: yellow
colorTo: purple
sdk: gradio
sdk_version: 5.45.0
app_file: app.py
pinned: true
license: mit

💕 thoshan_Flash - Complete Offline Package

A conversational Large language model with a fun, flirty personality. This repository includes everything you need for offline development and training - no cloud dependencies required!

🎁 What's Included

• Ready-to-run Gradio app (app.py) - No modifications needed
• Flirty tech dataset (flirt_dataset.jsonl) - 20 Q&A pairs for training
• Complete offline setup - All dependencies clearly listed
• Zero cloud dependencies - Works entirely on your local machine
• Copy-paste ready - All commands tested and ready to use

📦 Download & Quick Start

Option 1: Clone Everything

# Clone the complete repository
git clone https://huggingface.co/spaces/lingadevaruhp/thoshan_Flash_mini
cd thoshan_Flash_mini

# Install dependencies (one command, no conflicts)
pip install transformers torch gradio accelerate

# Run immediately
python app.py

Option 2: Download Just the Dataset

Get the dataset file directly for your own projects:

• Raw JSONL: flirt_dataset.jsonl
• Direct download: Right-click → "Save as" or use wget

# Download dataset only
wget https://huggingface.co/spaces/lingadevaruhp/thoshan_Flash_mini/raw/main/flirt_dataset.jsonl

🔥 Using the Dataset (Offline Training)

The flirt_dataset.jsonl file contains 20 flirty tech Q&A pairs in standard format:

{"instruction": "Hey gorgeous, explain machine learning to me", "response": "Aww, you're so cute when you're curious! 💕 Think of machine learning like..."}

Load in Python (Copy-Paste Ready)

import json

# Load the dataset
with open('flirt_dataset.jsonl', 'r') as f:
    dataset = [json.loads(line) for line in f]

print(f"Loaded {len(dataset)} flirty tech examples!")
for item in dataset[:2]:  # Show first 2
    print(f"Q: {item['instruction']}")
    print(f"A: {item['response'][:100]}...\n")

Use with Popular Training Libraries

# With Hugging Face datasets
from datasets import load_dataset
dataset = load_dataset('json', data_files='flirt_dataset.jsonl')

# With pandas
import pandas as pd
df = pd.read_json('flirt_dataset.jsonl', lines=True)

# Direct training format
training_data = []
with open('flirt_dataset.jsonl', 'r') as f:
    for line in f:
        data = json.loads(line)
        training_data.append({
            'input': data['instruction'],
            'output': data['response']
        })

💻 Model Information

• Base Model: thoshan_Flash
• No fine-tuning required - Works out of the box
• Public model - No API keys or special access needed
• Lightweight - Runs on consumer GPUs (4GB+ VRAM recommended)
• Fast inference - Optimized for real-time chat

🚀 Advanced Usage

Custom Training with Your Data

# Combine with your own data
my_data = []
with open('flirt_dataset.jsonl', 'r') as f:
    my_data.extend([json.loads(line) for line in f])

# Add your own examples
my_data.append({
    "instruction": "Your custom question",
    "response": "Your custom flirty response"
})

# Save combined dataset
with open('my_custom_dataset.jsonl', 'w') as f:
    for item in my_data:
        f.write(json.dumps(item) + '\n')

Fine-tune Locally (Optional)

# Example fine-tuning setup (requires additional setup)
from transformers import AutoTokenizer, AutoModelForCausalLM
from transformers import TrainingArguments, Trainer

model_name = "thoshan_Flash"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Your fine-tuning code here...

🛠️ Troubleshooting

Common Issues & Solutions

"Model not found" → Check internet connection for first download

pip install --upgrade transformers torch

"Out of memory" → Reduce batch size or use CPU mode

# In app.py, add:
device = "cpu"  # Force CPU usage

"Gradio won't start" → Update Gradio

pip install --upgrade gradio

"Dataset won't load" → Verify file format

# Check if file is valid JSON lines
python -c "import json; [json.loads(line) for line in open('flirt_dataset.jsonl')]; print('Valid!')"

📝 Dataset Details

Content: 20 technology-themed Q&A pairs with flirty, fun responses Topics covered: Machine learning, web development, databases, DevOps, security, and more Format: Standard JSONL (one JSON object per line) Size: ~10.4KB - Perfect for quick experiments Style: Educational but playful - explains complex tech concepts with personality

🎯 Perfect For

• Learning AI development - Complete, working example
• Chatbot experimentation - Ready-made personality dataset
• Offline development - No API dependencies
• Educational projects - Fun way to learn tech concepts
• Fine-tuning practice - Small, manageable dataset

🔄 Updates & Versions

• Latest: Added complete offline dataset (flirt_dataset.jsonl)
• Improved: Zero-dependency local setup
• Fixed: All dependency conflicts resolved
• Added: Copy-paste ready code examples

---

Ready to get flirty with AI? Download, run, and start chatting! 💕