Model Trained Using AutoTrain

This model was trained using AutoTrain. For more information, please visit AutoTrain.

Usage

pip install peft

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import AutoPeftModelForCausalLM, PeftConfig

model_id = "Aryan-401/phi-3-mini-4k-instruct-finetune-guanaco"
peft_model=AutoPeftModelForCausalLM.from_pretrained(model_id)

model = peft_model.merge_and_unload()
tokenizer = AutoTokenizer.from_pretrained(model_id)

messages = [
    {"role": "user", "content": "What is the Value of Pi?"}
]
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

model = model.to(device).eval()

input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to(device), max_length= 1000)
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)

print(response)