Spaces:
Running
on
Zero
Running
on
Zero
Add files
Browse files- .pre-commit-config.yaml +55 -0
- .vscode/settings.json +21 -0
- LICENSE +21 -0
- README.md +1 -0
- app.py +136 -0
- requirements.txt +9 -0
- style.css +16 -0
.pre-commit-config.yaml
ADDED
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repos:
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v4.5.0
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hooks:
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- id: check-executables-have-shebangs
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- id: check-json
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- id: check-merge-conflict
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- id: check-shebang-scripts-are-executable
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- id: check-toml
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- id: check-yaml
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- id: end-of-file-fixer
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- id: mixed-line-ending
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args: ["--fix=lf"]
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- id: requirements-txt-fixer
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- id: trailing-whitespace
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- repo: https://github.com/myint/docformatter
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rev: v1.7.5
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hooks:
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- id: docformatter
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args: ["--in-place"]
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- repo: https://github.com/pycqa/isort
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rev: 5.12.0
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hooks:
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- id: isort
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args: ["--profile", "black"]
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- repo: https://github.com/pre-commit/mirrors-mypy
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rev: v1.6.1
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hooks:
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- id: mypy
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args: ["--ignore-missing-imports"]
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additional_dependencies:
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["types-python-slugify", "types-requests", "types-PyYAML"]
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- repo: https://github.com/psf/black
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rev: 23.10.0
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hooks:
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- id: black
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language_version: python3.10
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args: ["--line-length", "119"]
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- repo: https://github.com/kynan/nbstripout
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rev: 0.6.1
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hooks:
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- id: nbstripout
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args:
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[
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"--extra-keys",
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"metadata.interpreter metadata.kernelspec cell.metadata.pycharm",
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]
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- repo: https://github.com/nbQA-dev/nbQA
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rev: 1.7.0
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hooks:
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- id: nbqa-black
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- id: nbqa-pyupgrade
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args: ["--py37-plus"]
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- id: nbqa-isort
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args: ["--float-to-top"]
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.vscode/settings.json
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{
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"[python]": {
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"editor.defaultFormatter": "ms-python.black-formatter",
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"editor.formatOnType": true,
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"editor.codeActionsOnSave": {
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"source.organizeImports": true
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}
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},
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"black-formatter.args": [
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"--line-length=119"
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],
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"isort.args": ["--profile", "black"],
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"flake8.args": [
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"--max-line-length=119"
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],
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"ruff.args": [
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"--line-length=119"
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],
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"editor.formatOnSave": true,
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"files.insertFinalNewline": true
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}
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LICENSE
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MIT License
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Copyright (c) 2023 hysts
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
CHANGED
@@ -8,6 +8,7 @@ sdk_version: 3.50.2
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app_file: app.py
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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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app_file: app.py
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pinned: false
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license: mit
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suggested-hardware: t4-small
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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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#!/usr/bin/env python
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import os
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from threading import Thread
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from typing import Iterator
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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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DESCRIPTION = "# Zephyr-7B-alpha"
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if not torch.cuda.is_available():
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DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
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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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if torch.cuda.is_available():
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model_id = "HuggingFaceH4/zephyr-7b-alpha"
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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@spaces.GPU
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def generate(
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message: str,
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chat_history: list[tuple[str, str]],
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system_prompt: str = "",
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max_new_tokens: int = 1024,
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temperature: float = 0.7,
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top_p: float = 0.95,
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top_k: int = 50,
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repetition_penalty: float = 1.0,
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) -> Iterator[str]:
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conversation = []
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if system_prompt:
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conversation.append({"role": "system", "content": system_prompt})
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for user, assistant in chat_history:
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conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
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conversation.append({"role": "user", "content": message})
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input_ids = tokenizer.apply_chat_template(conversation, return_tensors="pt", add_generation_prompt=True)
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if input_ids.shape[1] > MAX_INPUT_TOKEN_LENGTH:
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input_ids = input_ids[:, -MAX_INPUT_TOKEN_LENGTH:]
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gr.Warning(f"Trimmed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens.")
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input_ids = input_ids.to(model.device)
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streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
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generate_kwargs = dict(
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{"input_ids": input_ids},
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streamer=streamer,
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max_new_tokens=max_new_tokens,
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do_sample=True,
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top_p=top_p,
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top_k=top_k,
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temperature=temperature,
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num_beams=1,
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repetition_penalty=repetition_penalty,
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)
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t = Thread(target=model.generate, kwargs=generate_kwargs)
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t.start()
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outputs = []
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for text in streamer:
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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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gr.Textbox(
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label="System prompt",
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lines=6,
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placeholder="You are a friendly chatbot who always responds in the style of a pirate.",
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),
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gr.Slider(
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label="Max new tokens",
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minimum=1,
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maximum=MAX_MAX_NEW_TOKENS,
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step=1,
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value=DEFAULT_MAX_NEW_TOKENS,
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),
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gr.Slider(
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label="Temperature",
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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=0.7,
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),
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gr.Slider(
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label="Top-p (nucleus sampling)",
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minimum=0.05,
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maximum=1.0,
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step=0.05,
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value=0.95,
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),
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gr.Slider(
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label="Top-k",
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minimum=1,
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maximum=1000,
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step=1,
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value=50,
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),
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gr.Slider(
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label="Repetition penalty",
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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=1.0,
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),
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],
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stop_btn=None,
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examples=[
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["Hello there! How are you doing?"],
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["Can you explain briefly to me what is the Python programming language?"],
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["Explain the plot of Cinderella in a sentence."],
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["How many hours does it take a man to eat a Helicopter?"],
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["Write a 100-word article on 'Benefits of Open-Source in AI research'"],
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],
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)
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with gr.Blocks(css="style.css") as demo:
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gr.Markdown(DESCRIPTION)
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gr.DuplicateButton(
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value="Duplicate Space for private use",
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elem_id="duplicate-button",
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visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
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)
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chat_interface.render()
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if __name__ == "__main__":
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demo.queue(max_size=20).launch()
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requirements.txt
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accelerate==0.23.0
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bitsandbytes==0.41.1
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gradio==3.50.2
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protobuf==3.20.3
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scipy==1.11.2
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sentencepiece==0.1.99
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spaces==0.16.3
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torch==2.0.0
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transformers==4.34.1
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style.css
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h1 {
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text-align: center;
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}
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#duplicate-button {
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margin: auto;
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color: white;
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background: #1565c0;
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border-radius: 100vh;
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}
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.contain {
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max-width: 900px;
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margin: auto;
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padding-top: 1.5rem;
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}
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