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Upload 4 files
Browse files- README.md +6 -4
- app (3).py +89 -0
- gitattributes.txt +35 -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: gray
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colorTo:
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sdk: gradio
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sdk_version: 4.44.0
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app_file: app.py
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pinned: false
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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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---
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title: Jady
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emoji: 📚
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colorFrom: gray
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colorTo: blue
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sdk: gradio
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sdk_version: 4.44.0
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app_file: app.py
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pinned: false
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short_description: .
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license: mit
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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 (3).py
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from huggingface_hub import InferenceClient
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import gradio as gr
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from deep_translator import GoogleTranslator
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# Initialize the InferenceClient and the translators
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client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
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translator_to_en = GoogleTranslator(source='arabic', target='english')
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translator_to_ar = GoogleTranslator(source='english', target='arabic')
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def format_prompt(message, history):
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prompt = """<s> I want you to act as an intelligent tool developed by Mujahed, Mujahed Yemeni Communications Engineer. works in Wi-Fi network service and provides VPN service." """
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for user_prompt, bot_response in history:
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prompt += f"[INST] {user_prompt} [/INST]"
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prompt += f" {bot_response}</s> "
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prompt += f"[INST] {message} [/INST]"
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return prompt
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def generate(prompt, history, temperature=0.1, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
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temperature = float(temperature)
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if temperature < 1e-2:
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temperature = 1e-2
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top_p = float(top_p)
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generate_kwargs = dict(
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temperature=temperature,
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max_new_tokens=max_new_tokens,
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top_p=top_p,
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repetition_penalty=repetition_penalty,
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do_sample=True,
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seed=42,
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)
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# Translate the Arabic prompt to English
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translated_prompt = translator_to_en.translate(prompt)
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formatted_prompt = format_prompt(translated_prompt, history)
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stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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yield translator_to_ar.translate(output) # Translate the response back to Arabic
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return output
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additional_inputs=[
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gr.Slider(
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label="Temperature",
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value=0.7,
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minimum=0.0,
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maximum=1.0,
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step=0.05,
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interactive=True,
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info="Higher values produce more diverse outputs",
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),
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gr.Slider(
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label="Max new tokens",
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value=256,
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minimum=0,
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maximum=1048,
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step=64,
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interactive=True,
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info="The maximum numbers of new tokens",
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),
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gr.Slider(
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label="Top-p (nucleus sampling)",
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value=0.95,
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minimum=0.0,
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maximum=1,
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step=0.05,
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interactive=True,
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info="Higher values sample more low-probability tokens",
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),
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gr.Slider(
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label="Repetition penalty",
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value=1.2,
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minimum=1.0,
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maximum=2.0,
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step=0.05,
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interactive=True,
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info="Penalize repeated tokens",
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)
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]
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gr.ChatInterface(
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fn=generate,
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chatbot=gr.Chatbot(show_label=False, show_share_button=True, show_copy_button=True, likeable=True, layout="panel"),
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additional_inputs=additional_inputs,
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title="لازال تحت الاختبار اخوكم مجاهد الجعدي.. لا تتردد باي سؤال"
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).launch(show_api=False)
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gitattributes.txt
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bz2 filter=lfs diff=lfs merge=lfs -text
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*.ckpt filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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*.joblib filter=lfs diff=lfs merge=lfs -text
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.mlmodel filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.npy filter=lfs diff=lfs merge=lfs -text
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*.pickle filter=lfs diff=lfs merge=lfs -text
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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requirements.txt
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gradio
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huggingface-hub
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deep_translator
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