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Running
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Zero
Update app.py
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app.py
CHANGED
@@ -6,29 +6,16 @@ import gradio as gr
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import spaces
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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MAX_MAX_NEW_TOKENS = 2048
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DEFAULT_MAX_NEW_TOKENS = 1024
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MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
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DESCRIPTION = """\
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# Llama-
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This Space demonstrates model [Llama-2-13b-chat](https://huggingface.co/meta-llama/Llama-2-13b-chat) by Meta, a Llama 2 model with 13B parameters fine-tuned for chat instructions. Feel free to play with it, or duplicate to run generations without a queue! If you want to run your own service, you can also [deploy the model on Inference Endpoints](https://huggingface.co/inference-endpoints).
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🔎 For more details about the Llama 2 family of models and how to use them with `transformers`, take a look [at our blog post](https://huggingface.co/blog/llama2).
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🔨 Looking for an even more powerful model? Check out the large [**70B** model demo](https://huggingface.co/spaces/ysharma/Explore_llamav2_with_TGI).
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🐇 For a smaller model that you can run on many GPUs, check our [7B model demo](https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat).
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"""
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LICENSE = """
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<p/>
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---
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As a derivate work of [Llama-2-13b-chat](https://huggingface.co/meta-llama/Llama-2-13b-chat) by Meta,
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this demo is governed by the original [license](https://huggingface.co/spaces/huggingface-projects/llama-2-13b-chat/blob/main/LICENSE.txt) and [acceptable use policy](https://huggingface.co/spaces/huggingface-projects/llama-2-13b-chat/blob/main/USE_POLICY.md).
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"""
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if not torch.cuda.is_available():
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@@ -42,6 +29,26 @@ if torch.cuda.is_available():
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tokenizer.use_default_system_prompt = False
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@spaces.GPU
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def generate(
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message: str,
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outputs.append(text)
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yield "".join(outputs)
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chat_interface = gr.ChatInterface(
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fn=generate,
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additional_inputs=[
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@@ -103,7 +114,7 @@ chat_interface = gr.ChatInterface(
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minimum=0.1,
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maximum=4.0,
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step=0.1,
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value=0.
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),
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gr.Slider(
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label="Top-p (nucleus sampling)",
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@@ -124,7 +135,7 @@ chat_interface = gr.ChatInterface(
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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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value=1.
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),
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],
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stop_btn=None,
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import spaces
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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import sqlite3
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MAX_MAX_NEW_TOKENS = 2048
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DEFAULT_MAX_NEW_TOKENS = 1024
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MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
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DESCRIPTION = """\
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# Llama-3 7B MRC \
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"""
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if not torch.cuda.is_available():
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tokenizer.use_default_system_prompt = False
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_TABLE = """
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CREATE TABLE IF NOT EXISTS Item(
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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question TEXT NOT NULL,
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answer TEXT NOT NULL,
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timestamp TIMESTAMP DEFAULT (DATETIME('now', 'localtime'))
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);
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"""
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INSERT = """
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INSERT INTO Item(question, answer) VALUES(?, ?);
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"""
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connect = sqlite3.connect(db_path, check_same_thread=False)
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cursor = self.connect.cursor()
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cursor.execute(_TABLE)
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connect.commit()
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@spaces.GPU
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def generate(
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message: str,
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outputs.append(text)
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yield "".join(outputs)
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self.cursor.execute(INSERT, (message, "".join(outputs)))
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self.connect.commit()
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chat_interface = gr.ChatInterface(
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fn=generate,
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additional_inputs=[
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minimum=0.1,
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maximum=4.0,
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step=0.1,
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value=0.1,
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),
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gr.Slider(
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label="Top-p (nucleus sampling)",
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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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value=1.15,
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),
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],
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stop_btn=None,
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