Merge branch 'main' into vocquant

Author: stephantul

.github/workflows/ci.yaml

@@ -10,14 +10,16 @@ jobs:
     strategy:
       matrix:
         os: ["ubuntu-latest", "windows-latest"]
-        python-version: ["3.9", "3.10", "3.11", "3.12"]
+        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
         exclude:
           - os: windows-latest
             python-version: "3.9"
           - os: windows-latest
             python-version: "3.11"
           - os: windows-latest
             python-version: "3.12"
+          - os: windows-latest
+            python-version: "3.13"
       fail-fast: false
 
     steps:
@@ -55,7 +57,7 @@ jobs:
       # Run tests with coverage
       - name: Run tests under coverage
         run: |
-          coverage run -m pytest
+          coverage run --source=model2vec -m pytest
           coverage report
 
       # Upload results to Codecov

Makefile

@@ -10,7 +10,6 @@ install:
 
 install-no-pre-commit:
 	uv pip install ".[dev,distill,inference,train]"
-	uv pip install "torch<2.5.0"
 
 install-base:
 	uv sync --extra dev

README.md

@@ -92,7 +92,7 @@ m2v_model.save_pretrained("m2v_model")
 After distillation, you can also fine-tune your own classification models on top of the distilled model, or on a pre-trained model. First, make sure you install the `training` extras with:
 
 ```bash
-pip install model2vec[training]
+pip install model2vec[train]
 ```
 
 Then, you can fine-tune a model as follows:

model2vec/train/README.md

@@ -9,7 +9,7 @@ We support both single and multi-label classification, which work seamlessly bas
 To train, make sure you install the training extra:
 
 ```
-pip install model2vec[training]
+pip install model2vec[train]
 ```
 
 # Quickstart

pyproject.toml

@@ -19,6 +19,7 @@ classifiers = [
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
     "Natural Language :: English",
 ]