File size: 2,000 Bytes
590f94a 8fc411c 590f94a 8fc411c 590f94a 8fc411c 590f94a 8fc411c 1e7b8f1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
from transformers import pipeline, Conversation
import gradio as gr
from datetime import datetime
from transformers.utils import logging
logging.set_verbosity_error()
# Info about ['google/gemma-2b-it'](https://huggingface.co/google/gemma-2b-it)
chatbot = pipeline(task="conversational",
model="./models/google/gemma-2b-it")
def get_job_description(company_name, sector, job_position):
start_time = datetime.now()
messages = [
{
"role": "user",
"content": f"""
You are the Talent Acquisition Manager at { company_name }, a company of the { sector } sector.
Your goal is to hire people in different departments of the company.
I want to generate a Job Description for the role '{ job_position }' in a creative, modern, formal and attractive way.
"""
},
{
"role": "assistant",
"content": "Description:"
}
]
conversation = Conversation(messages)
conversation = chatbot(conversation, do_sample=True, max_new_tokens=600, temperature=1)
response = conversation.messages[-1]["content"]
delta_time = datetime.now() - start_time
return response, delta_time
with gr.Blocks() as demo:
gr.Markdown(
"""
# Job Description generator
### This SLM demo uses ['google/gemma-2b-it'](https://huggingface.co/google/gemma-2b-it)
""")
interface = gr.Interface(
fn = get_job_description,
inputs = [gr.Textbox(placeholder="Enter the company name", label="Company name"),
gr.Textbox(placeholder="Enter the company sector", label="Company sector"),
gr.Textbox(placeholder="Enter the job position", label="Job position")],
outputs = [gr.Markdown(),
gr.Textbox(label="Elapsed time")]
)
demo.launch(server_port=7860)
# demo.launch(share=True, server_port=7860)
|