rajatverma777/voice-ai-interview-gpt2

Voice AI Interview — Fine-Tuned DistilGPT2

A causal language model fine-tuned on structured mock interview prompt-completion pairs for the Voice AI Interview project.

Model Details

• —Base Model: distilgpt2
• —Task: Text generation (AI interviewer responses)
• —Fine-tuned on: Custom structured interview Q&A dataset
• —Hardware: Apple Silicon MPS GPU via PyTorch
• —License: Apache 2.0

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("rajatverma777/voice-ai-interview-gpt2")
model = AutoModelForCausalLM.from_pretrained("rajatverma777/voice-ai-interview-gpt2")

prompt = "Interviewer: Explain what is a binary search tree.\nCandidate:"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=150)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Project

Part of the Voice AI Interview Assistant — a full-stack AI-powered mock interview platform.