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import gradio as gr |
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import spaces |
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import torch |
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import transformers |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "meta-llama/Meta-Llama-3-8B" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16,device_map="auto") |
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@spaces.GPU |
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def yes_man(message, history): |
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input_ids = tokenizer(message, return_tensors="pt").input_ids.to(model.device) |
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output = model.generate(input_ids, max_length=512, num_return_sequences=1) |
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detailed_prompt = tokenizer.decode(output[0], skip_special_tokens=True) |
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return detailed_prompt |
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gr.ChatInterface( |
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yes_man, |
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chatbot=gr.Chatbot(height=300), |
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textbox=gr.Textbox(placeholder="Enter message here", container=False, scale=7), |
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title="LLAMA 3 8B Chat", |
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description="Ask Yes Man any question", |
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theme="soft", |
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examples=["Hello", "Am I cool?", "Are tomatoes vegetables?"], |
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cache_examples=True, |
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retry_btn=None, |
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undo_btn="Delete Previous", |
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clear_btn="Clear", |
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).launch() |
