Implemented PEFT feature in CSModel class

.readthedocs.yaml

@@ -34,6 +34,48 @@ sphinx:
 #   install:
 #     - requirements: docs/requirements.txt
 
+# Declare the Python requirements required to build your documentation
+python:
+  install:
+    - requirements: docs/requirements.txt
+    - method: pip
+      path: .
+# Read the Docs configuration file for Sphinx projects
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+# Required
+version: 2
+
+# Set the OS, Python version and other tools you might need
+build:
+  os: ubuntu-22.04
+  tools:
+    python: "3.12"
+    # You can also specify other tool versions:
+    # nodejs: "20"
+    # rust: "1.70"
+    # golang: "1.20"
+
+# Build documentation in the "docs/" directory with Sphinx
+sphinx:
+  configuration: docs/source/conf.py
+  # You can configure Sphinx to use a different builder, for instance use the dirhtml builder for simpler URLs
+  # builder: "dirhtml"
+  # Fail on all warnings to avoid broken references
+  # fail_on_warning: true
+
+# Optionally build your docs in additional formats such as PDF and ePub
+# formats:
+#   - pdf
+#   - epub
+
+# Optional but recommended, declare the Python requirements required
+# to build your documentation
+# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
+# python:
+#   install:
+#     - requirements: docs/requirements.txt
+
 # Declare the Python requirements required to build your documentation
 python:
   install:

README.md

@@ -3,7 +3,7 @@
 [![Code License: Apache 2.0](https://img.shields.io/badge/license-Apache%20License%202.0-blue)](https://www.apache.org/licenses/LICENSE-2.0)
 [![PyPI version](https://badge.fury.io/py/cell2sentence.svg)](https://badge.fury.io/py/cell2sentence)
 [![DOI:10.1101/2025.04.14.648850](http://img.shields.io/badge/DOI-10.1101/2025.04.14.648850-B31B1B.svg)](https://doi.org/10.1101/2025.04.14.648850)
-[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/release/python-380/)
+[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/release/python-310020/)
 
 ![cell2sentence workflow image](c2s_overview_figure.png)
 
@@ -47,7 +47,7 @@ git clone https://github.com/vandijklab/cell2sentence.git
 
 Navigate a terminal into the root of the repository. Next, create an Anaconda environment using `python3` using [anaconda](https://docs.anaconda.com/anaconda/install/) with:
 ```bash
-conda create -n cell2sentence python=3.8
+conda create -n cell2sentence python=3.10
 ```
 
 Next, activate the environment:
@@ -62,7 +62,7 @@ make install
 
 This will install the latest development environment of cell2sentence, along with other pacakge dependendies. You can also install cell2sentence itself using `pip`:
 ```bash
-pip install cell2sentence==1.1.0
+pip install cell2sentence==1.2.0
 ```
 
 The C2S package will allow usage of the core functionalities of C2S, including inference using existing C2S models and finetuning your own C2S models on your own datasets.
@@ -86,6 +86,10 @@ The following notebooks provide guides on common workflows with C2S models. For
 | [c2s_tutorial_4_cell_type_prediction.ipynb](tutorials/c2s_tutorial_4_cell_type_prediction.ipynb) | Cell type prediction using C2S models
 | [c2s_tutorial_5_cell_generation.ipynb](tutorials/c2s_tutorial_5_cell_generation.ipynb) | Cell generation conditioned on cell type
 | [c2s_tutorial_6_cell_annotation_with_foundation_model.ipynb](tutorials/c2s_tutorial_6_cell_annotation_with_foundation_model.ipynb) | Cell type annotation with foundation model
+| [c2s_tutorial_7_custom_prompt_templates.ipynb](tutorials/c2s_tutorials_7_custom_prompt_templates.ipynb) | Custom Prompt Templates with C2S PromptFormatter class
+| [c2s_tutorial_8_multi_cell_tissue_prediction.ipynb](tutorials/c2s_tutorial_8_multi_cell_tissue_prediction.ipynb) | Classifying the Tissue based on Multiple cell sentences
+| [c2s_tutorial_9_natural_language_interpretation.ipynb](tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb) | Use the C2S model to generate insightful summaries for different sets of cells
+| [c2s_tutorial_10_perturbation_response_prediction.ipynb](tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb)|
 
 
 ## Model Zoo
@@ -111,7 +115,7 @@ each explain which model they use.
 - [x] Add tutorial notebooks for main C2S workflows: cell type prediction, cell generation
 - [x] Add multi-cell prompt formatting
 - [ ] Add support for legacy C2S-GPT-2 model prompts
-- [ ] Add parameter-efficient finetuning methods (LoRA)
+- [x] Add parameter-efficient finetuning methods (LoRA)
 
 
 ## License

docs/Makefile

@@ -20,3 +20,4 @@ help:
 	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
 
 # Example: sphinx-build -M html docs/source/ docs/build/
+

docs/make.bat

@@ -33,3 +33,4 @@ goto end
 
 :end
 popd
+

docs/source/csmodel.rst

@@ -1,3 +1,26 @@
+
+A CSModel object is a wrapper around a Cell2Sentence model, which tracks the path of the model 
+saved on disk. When needed, the model is loaded from the path on disk for inference or finetuning.
+The class contains utilities for model generation and cell embedding with a Huggingface backend.
+
+.. autofunction:: csmodel.CSModel
+
+.. autofunction:: csmodel.CSModel.__init__
+
+.. autofunction:: csmodel.CSModel.__str__
+
+.. autofunction:: csmodel.CSModel.fine_tune
+
+.. autofunction:: csmodel.CSModel.generate_from_prompt
+
+.. autofunction:: csmodel.CSModel.generate_from_prompt_batched
+
+.. autofunction:: csmodel.CSModel.embed_cell
+
+.. autofunction:: csmodel.CSModel.embed_cells_batched
+
+.. autofunction:: csmodel.CSModel.push_model_to_hub
+=======
 CSModel
 =======
 

setup.cfg

@@ -1,44 +1,49 @@
-[metadata]
-name = cell2sentence
-version = 1.2.0
-author = Syed Asad Rizvi
-author_email = [email protected]
-description = Cell2Sentence: Single-cell Analysis With LLMs
-long_description = file: README.md
-long_description_content_type = text/markdown
-url = https://github.com/vandijklab/cell2sentence
-license = 'BY-NC-ND'
-project_urls =
-    Bug Tracker = https://github.com/vandijklab/cell2sentence/issues
-classifiers =
-    Programming Language :: Python :: 3
-    Development Status :: 2 - Pre-Alpha
-    Operating System :: OS Independent
-
-[options]
-package_dir =
-    = src
-packages = find:
-python_requires = >=3.7
-install_requires =
-    torch
-    transformers
-    datasets
-    anndata
-    scanpy
-    numpy
-    pandas
-    scipy
-    tqdm
-    scikit-learn
-    jupyterlab
-    accelerate
-    plotnine
-    sphinx
-    sphinx-rtd-theme
-
-[options.packages.find]
-where = src
-
-[options.package_data]
+[metadata]
+name = cell2sentence
+version = 1.2.0
+author = Syed Asad Rizvi
+author_email = [email protected]
+description = Cell2Sentence: Single-cell Analysis With LLMs
+long_description = file: README.md
+long_description_content_type = text/markdown
+url = https://github.com/vandijklab/cell2sentence
+license = 'BY-NC-ND'
+project_urls =
+    Bug Tracker = https://github.com/vandijklab/cell2sentence/issues
+classifiers =
+    Programming Language :: Python :: 3
+    Development Status :: 2 - Pre-Alpha
+    Operating System :: OS Independent
+
+[options]
+package_dir =
+    = src
+packages = find:
+python_requires = >=3.10
+install_requires =
+    torch
+    transformers
+    peft
+    bitsandbytes
+    datasets
+    anndata
+    scanpy
+    numpy
+    pandas
+    scipy
+    tqdm
+    scikit-learn
+    jupyterlab
+    accelerate
+    plotnine
+    sphinx
+    sphinx-rtd-theme
+    tiktoken
+    sentencepiece
+    protobuf
+
+[options.packages.find]
+where = src
+
+[options.package_data]
 * = *.json