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| import sys | |
| sys.path.insert(0, './petals/') | |
| import transformers | |
| import streamlit as st | |
| # Import a Petals model | |
| # from src.client.remote_model import DistributedBloomForCausalLM | |
| MODEL_NAME = "bigscience/test-bloomd-6b3" # select model you like | |
| # INITIAL_PEERS = ["/ip4/193.106.95.184/tcp/31000/p2p/QmSg7izCDtowVTACbUmWvEiQZNY4wgCQ9T9Doo66K59X6q"] | |
| tokenizer = transformers.BloomTokenizerFast.from_pretrained(MODEL_NAME) | |
| model = transformers.BloomForCausalLM.from_pretrained(MODEL_NAME) | |
| text = st.text_input('Enter some text') | |
| max_new_tokens = st.slider('Select a value', min_value=1, max_value=100) | |
| if text: | |
| input_ids = tokenizer([text], return_tensors="pt").input_ids | |
| output = model.generate(input_ids, max_new_tokens=max_new_tokens) | |
| output_text = tokenizer.batch_decode(output) | |
| st.write(output_text) | |