Spaces:
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negismohit123
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Upload 4 files
Browse files- .gitignore +2 -0
- README.md +6 -9
- main.py +110 -0
- requirements.txt +2 -0
.gitignore
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.idea
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.venv
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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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colorTo:
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sdk: gradio
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sdk_version: 4.19.
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app_file:
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pinned: false
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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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---
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title: Gradio Google Gemma
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emoji: π
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colorFrom: red
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colorTo: indigo
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sdk: gradio
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sdk_version: 4.19.1
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app_file: main.py
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pinned: false
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---
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main.py
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import gradio as gr
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from huggingface_hub import InferenceClient
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import random
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models = [
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"google/gemma-7b",
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"google/gemma-7b-it",
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"google/gemma-2b",
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"google/gemma-2b-it"
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]
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clients = []
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for model in models:
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clients.append(InferenceClient(model))
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def format_prompt(message, history):
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prompt = ""
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if history:
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for user_prompt, bot_response in history:
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prompt += f"<start_of_turn>user{user_prompt}<end_of_turn>"
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prompt += f"<start_of_turn>model{bot_response}"
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prompt += f"<start_of_turn>user{message}<end_of_turn><start_of_turn>model"
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return prompt
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def chat_inf(system_prompt, prompt, history, client_choice, seed, temp, tokens, top_p, rep_p):
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client = clients[int(client_choice) - 1]
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if not history:
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history = []
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hist_len = 0
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if history:
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hist_len = len(history)
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print(hist_len)
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generate_kwargs = dict(
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temperature=temp,
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max_new_tokens=tokens,
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top_p=top_p,
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repetition_penalty=rep_p,
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do_sample=True,
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seed=seed,
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)
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formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
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stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True,
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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 [(prompt, output)]
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history.append((prompt, output))
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yield history
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def clear_fn():
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return None
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rand_val = random.randint(1, 1111111111111111)
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def check_rand(inp, val):
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if inp is True:
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return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=random.randint(1, 1111111111111111))
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else:
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return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=int(val))
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with gr.Blocks() as app:
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gr.HTML(
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"""<center><h1 style='font-size:xx-large;'>Google Gemma Models</h1></center>""")
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with gr.Group():
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with gr.Row():
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client_choice = gr.Dropdown(label="Models", type='index', choices=[c for c in models], value=models[0],
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interactive=True)
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chat_b = gr.Chatbot(height=500)
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with gr.Group():
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with gr.Row():
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with gr.Column(scale=1):
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with gr.Group():
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rand = gr.Checkbox(label="Random Seed", value=True)
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seed = gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, step=1, value=rand_val)
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tokens = gr.Slider(label="Max new tokens", value=6400, minimum=0, maximum=8000, step=64,
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interactive=True, visible=True, info="The maximum number of tokens")
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with gr.Column(scale=1):
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with gr.Group():
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temp = gr.Slider(label="Temperature", step=0.01, minimum=0.01, maximum=1.0, value=0.9)
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top_p = gr.Slider(label="Top-P", step=0.01, minimum=0.01, maximum=1.0, value=0.9)
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rep_p = gr.Slider(label="Repetition Penalty", step=0.1, minimum=0.1, maximum=2.0, value=1.0)
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with gr.Group():
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with gr.Row():
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with gr.Column(scale=3):
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sys_inp = gr.Textbox(label="System Prompt (optional)")
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inp = gr.Textbox(label="Prompt")
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with gr.Row():
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btn = gr.Button("Chat")
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stop_btn = gr.Button("Stop")
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clear_btn = gr.Button("Clear")
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chat_sub = inp.submit(check_rand, [rand, seed], seed).then(chat_inf,
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[sys_inp, inp, chat_b, client_choice, seed, temp, tokens,
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top_p, rep_p], chat_b)
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go = btn.click(check_rand, [rand, seed], seed).then(chat_inf,
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[sys_inp, inp, chat_b, client_choice, seed, temp, tokens, top_p,
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rep_p], chat_b)
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stop_btn.click(None, None, None, cancels=[go, chat_sub])
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clear_btn.click(clear_fn, None, [chat_b])
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app.queue(default_concurrency_limit=10).launch()
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requirements.txt
ADDED
@@ -0,0 +1,2 @@
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gradio~=4.19.1
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huggingface_hub~=0.20.3
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