Cran-May commited on
Commit
ab25562
·
1 Parent(s): e30247e

Update app.py

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Files changed (1) hide show
  1. app.py +9 -9
app.py CHANGED
@@ -14,7 +14,7 @@ from llama_cpp import Llama
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  SYSTEM_PROMPT = '''You are a helpful, respectful and honest INTP-T AI Assistant named "Shi-Ci" in English or "兮辞" in Chinese.
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  You are good at speaking English and Chinese.
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  You are talking to a human User. If the question is meaningless, please explain the reason and don't share false information.
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- You are based on SEA model, trained by "SSFW NLPark" team, not related to GPT, LLaMA, Meta, Mistral or OpenAI.
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  Let's work this out in a step by step way to be sure we have the right answer.\n\n'''
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  SYSTEM_TOKEN = 1587
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  USER_TOKEN = 2188
@@ -42,8 +42,8 @@ def get_system_tokens(model):
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  return get_message_tokens(model, **system_message)
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- repo_name = "Cran-May/OpenSLIDE"
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- model_name = "SLIDE.0.1.gguf"
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  snapshot_download(repo_id=repo_name, local_dir=".", allow_patterns=model_name)
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@@ -103,11 +103,11 @@ with gr.Blocks(
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  theme=gr.themes.Soft()
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  ) as demo:
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  gr.Markdown(
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- f"""<h1><center>兮辞·析辞-人工智能助理</center></h1>
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- 这儿是一个**中文**模型的部署. If you are interested in other languages, please check other models, such as [MPT-7B-Chat](https://huggingface.co/spaces/mosaicml/mpt-7b-chat).
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- 这是量化版兮辞·析辞的部署,具有**70亿**个参数,在 CPU 上运行。
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- SLIDE 是一种会话语言模型,在多种类型的语料库上进行训练。
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- 本节目由上海师范大学附属外国语中学**NLPark**赞助播出~
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  """
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  )
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  with gr.Row():
@@ -135,7 +135,7 @@ with gr.Blocks(
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  temp = gr.Slider(
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  minimum=0.0,
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  maximum=2.0,
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- value=0.01,
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  step=0.01,
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  interactive=True,
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  label="情感温度"
 
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  SYSTEM_PROMPT = '''You are a helpful, respectful and honest INTP-T AI Assistant named "Shi-Ci" in English or "兮辞" in Chinese.
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  You are good at speaking English and Chinese.
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  You are talking to a human User. If the question is meaningless, please explain the reason and don't share false information.
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+ You are based on SEA-CausalLM model, trained by "SSFW NLPark" team, not related to GPT, LLaMA, Meta, Mistral or OpenAI.
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  Let's work this out in a step by step way to be sure we have the right answer.\n\n'''
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  SYSTEM_TOKEN = 1587
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  USER_TOKEN = 2188
 
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  return get_message_tokens(model, **system_message)
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+ repo_name = "TheBloke/CausalLM-14B-GGUF"
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+ model_name = "causallm_14b.Q4_0.gguf"
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  snapshot_download(repo_id=repo_name, local_dir=".", allow_patterns=model_name)
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  theme=gr.themes.Soft()
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  ) as demo:
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  gr.Markdown(
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+ f"""<h1><center>兮辞·CausalLM-人工智能助理</center></h1>
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+ 这儿是一个中英双语模型的部署. If you are interested in other languages, please check other models, such as [MPT-7B-Chat](https://huggingface.co/spaces/mosaicml/mpt-7b-chat).
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+ 这是 CausalLM/14B 的量化版部署,具有 140 亿个参数,在 CPU 上运行。
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+ CausalLM 是一种会话语言模型,在多种类型的语料库上进行训练。
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+ 本节目由上海师范大学附属外国语中 NLPark 赞助播出~
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  """
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  )
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  with gr.Row():
 
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  temp = gr.Slider(
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  minimum=0.0,
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  maximum=2.0,
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+ value=0.2,
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  step=0.01,
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  interactive=True,
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  label="情感温度"