notfix

app.py

@@ -5,23 +5,19 @@ import transformers
 import streamlit as st
 
 # Import a Petals model
-from src.client.remote_model import DistributedBloomForCausalLM
+# 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"]
+# INITIAL_PEERS = ["/ip4/193.106.95.184/tcp/31000/p2p/QmSg7izCDtowVTACbUmWvEiQZNY4wgCQ9T9Doo66K59X6q"]
 
 tokenizer = transformers.BloomTokenizerFast.from_pretrained(MODEL_NAME)
-model = DistributedBloomForCausalLM.from_pretrained(
-    MODEL_NAME, 
-    initial_peers=INITIAL_PEERS, 
-).to("cpu")
+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:
-    model = DistributedBloomForCausalLM(MODEL_NAME, INITIAL_PEERS)
     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)