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app.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Sat Oct  5 16:41:22 2024
+
+@author: Admin
+"""
+
+import gradio as gr
+from transformers import pipeline
+import os
+from huggingface_hub import login
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+
+#chatbot = pipeline(model="NCSOFT/Llama-3-OffsetBias-8B")
+#token = os.getenv("HF_TOKEN")
+login(token = os.getenv('HF_TOKEN'))
+#chatbot = pipeline(model="meta-llama/Llama-3.2-1B")
+
+tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-1B-Instruct")
+model = AutoModelForCausalLM.from_pretrained(
+    "meta-llama/Llama-3.2-1B-Instruct",
+    device_map="auto",
+    torch_dtype="auto",
+)
+
+#chatbot = pipeline(model="facebook/blenderbot-400M-distill")
+
+message_list = []
+response_list = []
+
+
+def vanilla_chatbot(message, history):
+    inputs = tokenizer(message, return_tensors="pt").to("cpu")
+    with torch.no_grad():
+        outputs = model.generate(inputs.input_ids, max_length=100)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+    #conversation = chatbot(message)
+    
+    #return conversation[0]['generated_text']
+
+demo_chatbot = gr.ChatInterface(vanilla_chatbot, title="Vanilla Chatbot", description="Enter text to start chatting.")
+
+demo_chatbot.launch(True)

requirements.txt

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+gradio
+transformers
+torch
+huggingface_hub
+accelerate>=0.26.0'