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Update app.py
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app.py
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@@ -5,7 +5,7 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("ai4bharat/Airavata")
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model = AutoModelForCausalLM.from_pretrained("ai4bharat/Airavata")
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def
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# Tokenize input prompt and generate response
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inputs = tokenizer(prompt, return_tensors="pt", max_length=256, truncation=True)
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outputs = model.generate(**inputs)
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@@ -13,23 +13,22 @@ def generate_response(prompt):
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return response
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# Define Gradio
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iface = gr.
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)
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# Launch Gradio
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iface.launch()
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# import torch
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# from transformers import AutoTokenizer, AutoModelForCausalLM
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# import gradio as gr
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@@ -78,24 +77,24 @@ iface.launch()
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# return output_texts
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model_name = "ai4bharat/Airavata"
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tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side="left")
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tokenizer.pad_token = tokenizer.eos_token
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16).to(device)
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print(f"Loading model: {model_name}")
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examples = [
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]
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def chat_interface(input_prompts):
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gr.Interface(fn=chat_interface,
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tokenizer = AutoTokenizer.from_pretrained("ai4bharat/Airavata")
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model = AutoModelForCausalLM.from_pretrained("ai4bharat/Airavata")
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def chat_interface(prompt):
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# Tokenize input prompt and generate response
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inputs = tokenizer(prompt, return_tensors="pt", max_length=256, truncation=True)
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outputs = model.generate(**inputs)
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return response
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# Define Gradio Chat Interface
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iface = gr.ChatInterface(
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chat_model=chat_interface,
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title="GPT-2 Chat Interface",
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inputs=["text"],
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outputs=["text"],
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examples = [
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["मैं अपने समय प्रबंधन कौशल को कैसे सुधार सकता हूँ? मुझे पांच बिंदु बताएं।"],
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["मैं अपने समय प्रबंधन कौशल को कैसे सुधार सकता हूँ? मुझे पांच बिंदु बताएं और उनका वर्णन करें।"],
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],
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# Launch Gradio Chat Interface
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iface.launch()
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# import torch
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# from transformers import AutoTokenizer, AutoModelForCausalLM
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# import gradio as gr
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# return output_texts
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# model_name = "ai4bharat/Airavata"
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# tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side="left")
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# tokenizer.pad_token = tokenizer.eos_token
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# model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16).to(device)
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# print(f"Loading model: {model_name}")
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# examples = [
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# ["मैं अपने समय प्रबंधन कौशल को कैसे सुधार सकता हूँ? मुझे पांच बिंदु बताएं।"],
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# ["मैं अपने समय प्रबंधन कौशल को कैसे सुधार सकता हूँ? मुझे पांच बिंदु बताएं और उनका वर्णन करें।"],
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# ]
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# def chat_interface(input_prompts):
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# outputs = inference(input_prompts, model, tokenizer)
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# return outputs
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# gr.Interface(fn=chat_interface,
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# inputs="text",
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# outputs="text",
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# examples=examples,
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# title="CAMAI ChatBot").launch()
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