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import gradio as gr |
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import random |
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import time |
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from ctransformers import AutoModelForCausalLM |
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model = AutoModelForCausalLM.from_pretrained( |
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"manan05/mistral-7b-friends-v0.1.gguf", |
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model_file="mistralfriends-7b-v0.1.gguf", |
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model_type="mistral", |
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gpu_layers=0, |
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hf=True |
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) |
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from transformers import AutoTokenizer, pipeline |
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tokenizer = AutoTokenizer.from_pretrained("manan05/mistral-7b-friends") |
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generator = pipeline( |
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model=model, tokenizer=tokenizer, |
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task='text-generation', |
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max_new_tokens=50, |
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repetition_penalty=1.1 |
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) |
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with gr.Blocks() as demo: |
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chatbot = gr.Chatbot() |
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msg = gr.Textbox() |
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clear = gr.ClearButton([msg, chatbot]) |
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def respond(message, chat_history): |
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user_message = "<s>[INST] Given the following conversation context, generate the upcomming dialogue of Joey in his style. \n CONTEXT: Me: " + message + "[/INST]" |
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bot_message = generator(user_message[0]["generated_text"]) |
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chat_history.append((user_message, bot_message)) |
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time.sleep(2) |
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return "", chat_history |
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msg.submit(respond, [msg, chatbot], [msg, chatbot]) |
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demo.launch() |