virtual-professor

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

base_model = AutoModelForCausalLM.from_pretrained(
    "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
    torch_dtype=torch.float16,
    device_map="auto"
)

model = PeftModel.from_pretrained(
    base_model, 
    "christianmalonga/virtual-professor"
)

tokenizer = AutoTokenizer.from_pretrained(
    "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
)

prompt = """### Instruction:
What is photosynthesis?

### Response:
"""

inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

### Instruction:
{question}

### Response:
{answer}

@misc{malonga2025virtualprofessor,
  author = {Christian Malonga},
  title = {Virtual Professor AI: A Fine-tuned LLM 
           for Educational Assistance},
  year = {2025},
  publisher = {HuggingFace},
  url = {https://huggingface.co/christianmalonga/virtual-professor}
}