Merge branch 'main' of https://huggingface.co/spaces/MasterThesisCBS/NorPaca_GPT
Browse files- app.py +14 -13
- requirements.txt +2 -1
app.py
CHANGED
@@ -1,6 +1,7 @@
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import random
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import os
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from urllib.parse import urlencode
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import streamlit as st
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import streamlit.components.v1 as components
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@@ -18,9 +19,9 @@ print(
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HF_AUTH_TOKEN = "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"
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DEVICE = os.environ.get("cuda:0", "cpu") # cuda:0
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DTYPE = torch.float32 if DEVICE == "cpu" else torch.float16
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MODEL_NAME = os.environ.get("MODEL_NAME", "NbAiLab/nb-gpt-j-6B-
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MAX_LENGTH = int(os.environ.get("MAX_LENGTH", 256))
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-
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HEADER_INFO = """
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# CBS_Alpaca-GPT-j
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Norwegian GPT-J-6B NorPaca Model.
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@@ -203,20 +204,20 @@ def main():
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index=int(query_params.get("do_sample", ["true"])[
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0].lower()[0] in ("t", "y", "1")),
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)
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do_clean = st.sidebar.selectbox(
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)
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generation_kwargs = {
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"max_length": max_length,
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"top_k": top_k,
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"top_p": top_p,
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"temperature": temperature,
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"do_sample": do_sample,
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"do_clean": do_clean,
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}
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st.markdown(HEADER_INFO)
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prompts = EXAMPLES + ["Custom"]
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@@ -241,8 +242,8 @@ def main():
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for _ in range(5):
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generated_text = generator.generate(
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text, generation_kwargs)
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if do_clean:
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if generated_text.strip().startswith(text):
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generated_text = generated_text.replace(
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text, "", 1).strip()
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@@ -273,4 +274,4 @@ def main():
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if __name__ == '__main__':
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main()
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import random
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import os
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from urllib.parse import urlencode
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from pyngrok import ngrok
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import streamlit as st
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import streamlit.components.v1 as components
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HF_AUTH_TOKEN = "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"
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DEVICE = os.environ.get("cuda:0", "cpu") # cuda:0
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DTYPE = torch.float32 if DEVICE == "cpu" else torch.float16
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MODEL_NAME = os.environ.get("MODEL_NAME", "NbAiLab/nb-gpt-j-6B-alpaca")
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MAX_LENGTH = int(os.environ.get("MAX_LENGTH", 256))
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+
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HEADER_INFO = """
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# CBS_Alpaca-GPT-j
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Norwegian GPT-J-6B NorPaca Model.
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index=int(query_params.get("do_sample", ["true"])[
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0].lower()[0] in ("t", "y", "1")),
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)
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# do_clean = st.sidebar.selectbox(
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# label='Clean text?',
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# options=(False, True),
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# help="Whether or not to remove repeated words and trim unfinished last sentences.",
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# index=int(query_params.get("do_clean", ["true"])[
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# 0].lower()[0] in ("t", "y", "1")),
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# )
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generation_kwargs = {
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"max_length": max_length,
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"top_k": top_k,
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"top_p": top_p,
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"temperature": temperature,
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"do_sample": do_sample,
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# "do_clean": do_clean,
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}
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st.markdown(HEADER_INFO)
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prompts = EXAMPLES + ["Custom"]
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for _ in range(5):
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generated_text = generator.generate(
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text, generation_kwargs)
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# if do_clean:
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# generated_text = cleaner.clean_txt(generated_text)
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if generated_text.strip().startswith(text):
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generated_text = generated_text.replace(
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text, "", 1).strip()
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if __name__ == '__main__':
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main()
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requirements.txt
CHANGED
@@ -1,4 +1,5 @@
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--find-links https://download.pytorch.org/whl/torch_stable.html
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torch
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transformers
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urllib3
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--find-links https://download.pytorch.org/whl/torch_stable.html
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torch
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transformers
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urllib3
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pyngrok
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