scarse

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Author: Leo Andrekson, Robin Rydbergh, Rocío Mercado, Michaela Wenzel
License: MIT
Summary: A package for training SCARSE on small sample sizes of peptide sequences that can later be used to predict peptide properties of unseen peptides via regression. Making SCARSE perfectly suited for AI-infused peptide engineering.
Latest version: 2.0.0
Required dependencies: alembic | annotated-doc | anyio | asttokens | bottle | bottle-websocket | certifi | cffi | click | colorama | colorlog | comm | debugpy | decorator | executing | filelock | fsspec | future | gevent | gevent-websocket | greenlet | h11 | hf-xet | httpcore | httpx | huggingface-hub | idna | importlib-resources | ipykernel | ipython | ipython-pygments-lexers | jedi | jinja2 | joblib | jupyter-client | jupyter-core | mako | markdown-it-py | markupsafe | matplotlib-inline | mdurl | mpmath | nest-asyncio | networkx | numpy | optuna | packaging | pandas | parso | pillow | platformdirs | prompt-toolkit | psutil | pure-eval | pycparser | pygments | pyparsing | python-dateutil | pyyaml | pyzmq | regex | rich | safetensors | scikit-learn | scipy | setuptools | shellingham | six | sqlalchemy | stack-data | sympy | threadpoolctl | tokenizers | torch | torchvision | tornado | tqdm | traitlets | transformers | typer | typing-extensions | tzdata | wcwidth | zope-event | zope-interface

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