{\rtf1\ansi\ansicpg1252\cocoartf2867
\cocoatextscaling0\cocoaplatform0{\fonttbl\f0\fswiss\fcharset0 Helvetica;}
{\colortbl;\red255\green255\blue255;}
{\*\expandedcolortbl;;}
\paperw11900\paperh16840\margl1440\margr1440\vieww11520\viewh8400\viewkind0
\pard\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\pardirnatural\partightenfactor0

\f0\fs24 \cf0 Step1:\
!pip install -U transformers\
\
step2:\
from transformers import pipeline\
\
pipe = pipeline("text-generation", model="varuneshv/VCoder")\
messages = [\
    \{"role": "user", "content": "Who are you?"\},\
]\
pipe(messages)\
\
step3:\
\
from transformers import AutoTokenizer, AutoModelForCausalLM\
\
tokenizer = AutoTokenizer.from_pretrained("varuneshv/VCoder")\
\
model = AutoModelForCausalLM.from_pretrained(\
    "varuneshv/VCoder"\
)\
\
step4:\
\
inputs = tokenizer(\
    "write a python code to merge 3 arrays",\
    return_tensors="pt"\
)\
\
outputs = model.generate(\
    **inputs,\
    max_new_tokens=200\
)\
\
print(tokenizer.decode(outputs[0], skip_special_tokens=True))\
}