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Aspik101
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Duplicate from Aspik101/trurl-2-7b-pl-instruct_GGML
Browse files- .gitattributes +35 -0
- README.md +14 -0
- app.py +56 -0
- requirements.txt +4 -0
.gitattributes
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README.md
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---
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title: trurl-2-7b-pl-instruct_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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duplicated_from: Aspik101/trurl-2-7b-pl-instruct_GGML
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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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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from datetime import datetime
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params = {
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"max_new_tokens":512,
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"stop":["<end>" ,"<|endoftext|>","[", "<user>"],
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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-2-7b-pl-instruct_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 parse_history(hist):
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history_ = ""
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for q, a in hist:
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history_ += f"<user>: {q } \n"
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if a:
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history_ += f"<assistant>: {a} \n"
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return history_
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def bot(history):
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print(f"When: {datetime.today().strftime('%Y-%m-%d %H:%M:%S')}")
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print("history: ",history)
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prompt = f"Jesteś AI assystentem. Odpowiadaj po polsku. {parse_history(history)}. <assistant>:"
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print("prompt: ",prompt)
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stream = llm(prompt, **params)
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history[-1][1] = ""
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answer_save = ""
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for character in stream:
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history[-1][1] += character
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answer_save += character
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time.sleep(0.005)
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yield history
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print("answer_save: ",answer_save)
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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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dl-hf-model
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