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NativeVex
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merge develop.milestone-3
Browse filesmerge containing work on the actual milestone-3 and the renaming of the folder for multi-object tracking to the correct name. No adjustment to the branches will be done to preserve the hf space settings.
- README.md +16 -0
- language_models_project/__init__.py +0 -0
- language_models_project/app.py +45 -0
- language_models_project/main.py +12 -0
- requirements.txt +156 -0
README.md
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---
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title: Milestone 2
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emoji: 📹
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colorFrom: blue
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colorTo: red
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sdk: streamlit
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app_file: language_models_project/app.py
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python_version: 3.10.4
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pinned: false
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---
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# image2textapp
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demo of 🤗 spaces deployment of a streamlit python app
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deployed at https://huggingface.co/spaces/NativeVex/large-language-models
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language_models_project/__init__.py
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language_models_project/app.py
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import streamlit as st # Web App
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from main import classify
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demo_phrases = """ Here are some examples:
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this is a phrase
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is it neutral
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nothing else to say
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man I'm so damn angry
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sarcasm lol
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I love this product
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"""
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# title
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st.title("Sentiment Analysis")
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# subtitle
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st.markdown("## A selection of popular sentiment analysis models - hosted on 🤗 Spaces")
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model_name = st.selectbox(
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"Select a pre-trained model",
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[
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"finiteautomata/bertweet-base-sentiment-analysis",
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"ahmedrachid/FinancialBERT-Sentiment-Analysis",
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"finiteautomata/beto-sentiment-analysis",
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],
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)
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input_sentences = st.text_area("Sentences", value=demo_phrases, height=200)
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data = input_sentences.split("\n")
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if st.button("Classify"):
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st.write("Please allow a few minutes for the model to run/download")
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for i in range(len(data)):
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j = classify(model_name.strip(), data[i])[0]
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sentiment = j["label"]
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confidence = j["score"]
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st.write(
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f"{i}. {data[i]} :: Classification - {sentiment} with confidence {confidence}"
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)
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st.markdown(
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"Link to the app - [image-to-text-app on 🤗 Spaces](https://huggingface.co/spaces/Amrrs/image-to-text-app)"
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)
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language_models_project/main.py
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from transformers import pipeline
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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def classify(model_string: str, *args, **kwargs):
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tokenizer = AutoTokenizer.from_pretrained(model_string)
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model = AutoModelForSequenceClassification.from_pretrained(model_string)
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sentiment_pipeline = pipeline(
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"sentiment-analysis",
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model=model,
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tokenizer=tokenizer
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)
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return sentiment_pipeline(*args, **kwargs)
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requirements.txt
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aiofiles==22.1.0
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aiosqlite==0.18.0
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antlr4-python3-runtime==4.9.3
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anyconfig==0.10.1
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anyio==3.6.2
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argon2-cffi==21.3.0
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argon2-cffi-bindings==21.2.0
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arrow==1.2.3
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asttokens==2.2.1
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attrs==22.2.0
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Babel==2.12.1
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backcall==0.2.0
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beautifulsoup4==4.12.2
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binaryornot==0.4.4
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bleach==6.0.0
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build==0.10.0
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cachetools==5.3.0
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certifi==2022.12.7
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cffi==1.15.1
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chardet==5.1.0
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charset-normalizer==3.1.0
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click==8.1.3
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cmake==3.26.1
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comm==0.1.3
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cookiecutter==2.1.1
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debugpy==1.6.7
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decorator==5.1.1
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defusedxml==0.7.1
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dynaconf==3.1.12
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executing==1.2.0
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fastjsonschema==2.16.3
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filelock==3.11.0
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fqdn==1.5.1
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fsspec==2023.3.0
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gitdb==4.0.10
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GitPython==3.1.31
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huggingface-hub==0.13.4
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idna==3.4
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importlib-metadata==6.2.1
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importlib-resources==5.12.0
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ipykernel==6.22.0
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ipython==8.12.0
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ipython-genutils==0.2.0
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isoduration==20.11.0
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jedi==0.18.2
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Jinja2==3.1.2
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jinja2-time==0.2.0
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jmespath==0.10.0
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json5==0.9.11
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jsonpointer==2.3
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jsonschema==4.17.3
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jupyter-events==0.6.3
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jupyter-ydoc==0.2.3
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jupyter_client==8.1.0
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jupyter_core==5.3.0
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jupyter_server==2.5.0
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jupyter_server_fileid==0.9.0
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jupyter_server_terminals==0.4.4
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jupyter_server_ydoc==0.8.0
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jupyterlab==3.6.3
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jupyterlab-pygments==0.2.2
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jupyterlab_server==2.22.0
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kedro==0.18.7
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lit==16.0.0
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markdown-it-py==2.2.0
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MarkupSafe==2.1.2
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matplotlib-inline==0.1.6
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mdurl==0.1.2
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mistune==2.0.5
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more-itertools==9.1.0
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mpmath==1.3.0
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nbclassic==0.5.5
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nbclient==0.7.3
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nbconvert==7.3.0
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nbformat==5.8.0
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nest-asyncio==1.5.6
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networkx==3.1
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notebook==6.5.4
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notebook_shim==0.2.2
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numpy==1.24.2
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nvidia-cublas-cu11==11.10.3.66
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nvidia-cuda-cupti-cu11==11.7.101
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nvidia-cuda-nvrtc-cu11==11.7.99
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nvidia-cuda-runtime-cu11==11.7.99
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nvidia-cudnn-cu11==8.5.0.96
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nvidia-cufft-cu11==10.9.0.58
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nvidia-curand-cu11==10.2.10.91
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nvidia-cusolver-cu11==11.4.0.1
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nvidia-cusparse-cu11==11.7.4.91
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nvidia-nccl-cu11==2.14.3
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nvidia-nvtx-cu11==11.7.91
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omegaconf==2.3.0
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packaging==23.0
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pandas==2.0.0
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pandocfilters==1.5.0
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parso==0.8.3
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pexpect==4.8.0
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pickleshare==0.7.5
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pip-tools==6.13.0
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platformdirs==3.2.0
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pluggy==1.0.0
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prometheus-client==0.16.0
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prompt-toolkit==3.0.38
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104 |
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protobuf==3.20.3
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psutil==5.9.4
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ptyprocess==0.7.0
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107 |
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pure-eval==0.2.2
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pycparser==2.21
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Pygments==2.14.0
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pyproject_hooks==1.0.0
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pyrsistent==0.19.3
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112 |
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python-dateutil==2.8.2
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python-json-logger==2.0.7
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114 |
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python-slugify==8.0.1
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115 |
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pytoolconfig==1.2.5
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116 |
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pytz==2023.3
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PyYAML==6.0
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pyzmq==25.0.2
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regex==2023.3.23
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requests==2.28.2
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rfc3339-validator==0.1.4
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rfc3986-validator==0.1.1
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rich==13.3.3
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rope==1.7.0
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Send2Trash==1.8.0
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126 |
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sentencepiece==0.1.97
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127 |
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six==1.16.0
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128 |
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smmap==5.0.0
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129 |
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sniffio==1.3.0
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130 |
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soupsieve==2.4
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131 |
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stack-data==0.6.2
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132 |
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sympy==1.11.1
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133 |
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terminado==0.17.1
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text-unidecode==1.3
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135 |
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tinycss2==1.2.1
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136 |
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tokenizers==0.13.3
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137 |
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toml==0.10.2
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138 |
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tomli==2.0.1
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139 |
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toposort==1.10
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140 |
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torch==2.0.0
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141 |
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tornado==6.2
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142 |
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tqdm==4.65.0
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143 |
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traitlets==5.9.0
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144 |
+
transformers==4.27.4
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145 |
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triton==2.0.0
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146 |
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typing_extensions==4.5.0
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147 |
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tzdata==2023.3
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148 |
+
uri-template==1.2.0
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149 |
+
urllib3==1.26.15
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+
wcwidth==0.2.6
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webcolors==1.13
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152 |
+
webencodings==0.5.1
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153 |
+
websocket-client==1.5.1
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154 |
+
y-py==0.5.9
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155 |
+
ypy-websocket==0.8.2
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156 |
+
zipp==3.15.0
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