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Browse files- README.md +5 -5
- app.py +39 -0
- requirements.txt +3 -0
README.md
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---
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title:
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emoji:
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colorFrom:
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sdk: gradio
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sdk_version: 3.
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app_file: app.py
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pinned: false
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license: other
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---
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title: Polish trurl-2-13b-GGML
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emoji: 📚
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colorFrom: indigo
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colorTo: red
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sdk: gradio
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sdk_version: 3.38.0
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app_file: app.py
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pinned: false
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license: other
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app.py
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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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params = {
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"max_new_tokens":512,
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"stop":["<end>" ,"<|endoftext|>"],
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"temperature":0.7,
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"top_p":0.8,
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"stream":True,
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"batch_size": 8}
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llm = AutoModelForCausalLM.from_pretrained("Aspik101/trurl-2-13b-GGML", model_type="llama")
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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.Button("Clear")
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def user(user_message, history):
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return "", history + [[user_message, None]]
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def bot(history):
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stream = llm(prompt = f"Jesteś AI assystentem. Odpowiadaj po polski. <user>: {history}. <assistant>:", **params)
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history[-1][1] = ""
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for character in stream:
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history[-1][1] += character
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time.sleep(0.005)
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yield history
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msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
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bot, chatbot, chatbot
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)
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clear.click(lambda: None, None, chatbot, queue=False)
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demo.queue()
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demo.launch()
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requirements.txt
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torch
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ctransformers
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gradio
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