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Shubham1211/
aichatpro

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library_name: transformers license: mit base_model: gpt2 tags:

fine-tuned
conversational
chat
transformers
huggingface model-index:
name: aichatpro results: []

aichatpro

aichatpro is a fine-tuned version of gpt2 designed for conversational AI tasks.
It was trained using a custom dataset of user prompts and assistant responses to improve dialogue quality and make GPT-2 respond more naturally in chatbot scenarios.

Model description

Model type: Causal Language Model (GPT-2 architecture)
Language: English (can be adapted if dataset contains other languages)
Purpose: Conversational AI, chatbot systems, and interactive assistants.
Base model: gpt2
Fine-tuning method: Supervised fine-tuning on prompt–response pairs.

Intended uses & limitations

Intended uses

Building chatbots
Interactive Q&A systems
Prototyping conversational agents

Limitations

May produce incorrect or nonsensical answers
May reproduce biases from GPT-2 or training data
Not optimized for factual accuracy or real-time decision-making

Training and evaluation data

The dataset was built from structured conversation logs, pairing user prompts with assistant responses.
Preprocessing steps included:

Sorting messages by timestamp
Pairing user → assistant turns
Filtering out entries with bug/error-related keywords

Training procedure

Training hyperparameters

Learning rate: 5e-05
Train batch size: 4
Eval batch size: 8
Seed: 42
Optimizer: AdamW (betas=(0.9, 0.999), epsilon=1e-08)
Scheduler: Linear decay
Epochs: 3

Hardware

CPU / GPU supported
Model fine-tuned using Hugging Face Trainer API

Usage

Load and generate text

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "YourUsername/aichatpro"  # replace with your HF username/repo
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = "Hello! How are you today?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=50)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Shubham1211/aichatpro