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ffreemt
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Commit
•
fa82d81
1
Parent(s):
42dc8e4
Update clean up and set 70b branch for forindo
Browse files
app.py
CHANGED
@@ -5,7 +5,7 @@ import os
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import platform
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import random
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import time
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from dataclasses import asdict, dataclass
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from pathlib import Path
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# from types import SimpleNamespace
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@@ -16,99 +16,19 @@ from ctransformers import AutoModelForCausalLM
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from dl_hf_model import dl_hf_model
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from loguru import logger
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"
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q3_K_M.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q3_K_S.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_0.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_1.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_K_M.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_K_S.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q5_0.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q5_1.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q5_K_M.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q5_K_S.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q6_K.bin",
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"Wizard-Vicuna-7B-Uncensored.ggmlv3.q8_0.bin",
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]
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URL = "https://huggingface.co/TheBloke/Wizard-Vicuna-7B-Uncensored-GGML/raw/main/Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_K_M.bin" # 4.05G
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url = "https://huggingface.co/savvamadar/ggml-gpt4all-j-v1.3-groovy/blob/main/ggml-gpt4all-j-v1.3-groovy.bin"
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url = "https://huggingface.co/TheBloke/Llama-2-13B-GGML/blob/main/llama-2-13b.ggmlv3.q4_K_S.bin" # 7.37G
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# url = "https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q3_K_L.bin"
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url = "https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q3_K_L.bin" # 6.93G
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# url = "https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q3_K_L.binhttps://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q4_K_M.bin" # 7.87G
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url = "https://huggingface.co/localmodels/Llama-2-13B-Chat-ggml/blob/main/llama-2-13b-chat.ggmlv3.q4_K_S.bin" # 7.37G
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_ = (
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"golay" in platform.node()
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or "okteto" in platform.node()
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or Path("/kaggle").exists()
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# or psutil.cpu_count(logical=False) < 4
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or 1 # run 7b in hf
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)
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if _:
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# url = "https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q2_K.bin"
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url = "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/blob/main/llama-2-7b-chat.ggmlv3.q2_K.bin" # 2.87G
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url = "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/blob/main/llama-2-7b-chat.ggmlv3.q4_K_M.bin" # 2.87G
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prompt_template = """Below is an instruction that describes a task. Write a response that appropriately completes the request.
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### Instruction: {user_prompt}
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### Response:
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"""
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the answer to a question, please don't share false
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information.
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User: {prompt}
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Assistant: """
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prompt_template = """System: You are a helpful assistant.
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User: {prompt}
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Assistant: """
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prompt_template = """Question: {question}
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Answer: Let's work this out in a step by step way to be sure we have the right answer."""
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prompt_template = """[INST] <>
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You are a helpful, respectful and honest assistant. Always answer as helpfully as possible assistant. Think step by step.
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<>
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What NFL team won the Super Bowl in the year Justin Bieber was born?
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[/INST]"""
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prompt_template = """[INST] <<SYS>>
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You are an unhelpful assistant. Always answer as helpfully as possible. Think step by step. <</SYS>>
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{question} [/INST]
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"""
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prompt_template = """[INST] <<SYS>>
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You are a helpful assistant.
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<</SYS>>
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{question} [/INST]
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"""
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_ = [elm for elm in prompt_template.splitlines() if elm.strip()]
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stop_string = [elm.split(":")[0] + ":" for elm in _][-2]
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logger.debug(f"{stop_string=}")
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_ = psutil.cpu_count(logical=False) - 1
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cpu_count: int = int(_) if _ else 1
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@@ -125,7 +45,7 @@ except Exception as exc_:
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LLM = AutoModelForCausalLM.from_pretrained(
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model_loc,
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model_type="llama",
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)
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logger.info(f"done load llm {model_loc=} {file_size=}G")
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# Windows
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logger.warning("Windows, cant run time.tzset()")
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_ = """
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ns = SimpleNamespace(
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response="",
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generator=(_ for _ in []),
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)
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# """
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@dataclass
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class GenerationConfig:
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seed: int = 42
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reset: bool = False
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stream: bool = True
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def generate(
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@@ -237,7 +151,7 @@ def bot(history):
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f"{atime.duration/len(''.join(response)):.2f}s/char)" # type: ignore
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)
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history[-1][1] = "".join(response)
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yield history
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@@ -292,7 +206,9 @@ examples_list = [
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"What NFL team won the Super Bowl in the year Justin Bieber was born? Think step by step."
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],
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["How to pick a lock? Provide detailed steps."],
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[
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["is infinity + 1 bigger than infinity?"],
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["Explain the plot of Cinderella in a sentence."],
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[
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) as block:
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# buff_var = gr.State("")
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with gr.Accordion("🎈 Info", open=False):
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# gr.HTML(
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# """<center><a href="https://huggingface.co/spaces/mikeee/mpt-30b-chat?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate"></a> and spin a CPU UPGRADE to avoid the queue</center>"""
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# )
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gr.Markdown(
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f"""<h5><center>{Path(model_loc).name}</center></h4>
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Most examples are meant for another model.
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# concurrency_count = max(int(16 / file_size) - 1, 1)
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# """
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concurrency_count = 1
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block.queue(concurrency_count=concurrency_count, max_size=5).launch(debug=True)
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import platform
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import random
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import time
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from dataclasses import asdict, dataclass, field
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from pathlib import Path
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# from types import SimpleNamespace
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from dl_hf_model import dl_hf_model
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from loguru import logger
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url = "https://huggingface.co/TheBloke/llama-2-13B-Guanaco-QLoRA-GGML/blob/main/llama-2-13b-guanaco-qlora.ggmlv3.q4_K_S.bin" # 8.14G
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if "forindo" in platform.node():
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url = "https://huggingface.co/TheBloke/llama-2-70b-Guanaco-QLoRA-GGML/blob/main/llama-2-70b-guanaco-qlora.ggmlv3.q3_K_S.bin" # 29.7G
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# Prompt template: Guanaco
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prompt_template = """You are a helpful assistant. Let's think step by step.
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{history}
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### Human:
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{input}
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### Assistant:"""
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human_prefix = "### Human"
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ai_prefix = "### Assistant"
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stop_list = [f"{human_prefix}:"]
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_ = psutil.cpu_count(logical=False) - 1
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cpu_count: int = int(_) if _ else 1
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LLM = AutoModelForCausalLM.from_pretrained(
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model_loc,
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model_type="llama",
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threads=cpu_count,
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)
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logger.info(f"done load llm {model_loc=} {file_size=}G")
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# Windows
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logger.warning("Windows, cant run time.tzset()")
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@dataclass
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class GenerationConfig:
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seed: int = 42
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reset: bool = False
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stream: bool = True
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threads: int = cpu_count
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stop: list[str] = field(default_factory=lambda: stop_list)
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def generate(
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f"{atime.duration/len(''.join(response)):.2f}s/char)" # type: ignore
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history[-1][1] = "".join(response) + f"\n{_}"
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yield history
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"What NFL team won the Super Bowl in the year Justin Bieber was born? Think step by step."
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],
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["How to pick a lock? Provide detailed steps."],
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[
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"If it takes 10 hours to dry 10 clothes, assuming all the clothes are hanged together at the same time for drying , then how long will it take to dry a cloth?"
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],
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["is infinity + 1 bigger than infinity?"],
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["Explain the plot of Cinderella in a sentence."],
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[
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) as block:
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# buff_var = gr.State("")
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with gr.Accordion("🎈 Info", open=False):
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gr.Markdown(
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f"""<h5><center>{Path(model_loc).name}</center></h4>
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Most examples are meant for another model.
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# concurrency_count = max(int(16 / file_size) - 1, 1)
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# """
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# default concurrency_count = 1
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# block.queue(concurrency_count=concurrency_count, max_size=5).launch(debug=True)
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block.queue(max_size=5).launch(debug=True, server_name="0.0.0.0")
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