Remove examples

.circleci/create_circleci_config.py

@@ -174,10 +174,7 @@ def to_dict(self):
             f"--{key}={value}" if (value is not None or key in ["doctest-modules"]) else f"-{key}"
             for key, value in all_options.items()
         ]
-        pytest_flags.append(
-            f"--make-reports={self.name}" if "examples" in self.name else f"--make-reports=tests_{self.name}"
-        )
-        # Examples special case: we need to download NLTK files in advance to avoid cuncurrency issues
+        pytest_flags.append(f"--make-reports=tests_{self.name}")
         timeout_cmd = f"timeout {self.command_timeout} " if self.command_timeout else ""
         marker_cmd = f"-m '{self.marker}'" if self.marker is not None else ""
         junit_flags = " -p no:warning -o junit_family=xunit1 --junitxml=test-results/junit.xml"
@@ -189,14 +186,6 @@ def to_dict(self):
             {"attach_workspace": {"at": "test_preparation"}},
             {"run": "apt-get update && apt-get install -y curl"},
             {"run": " && ".join(self.install_steps)},
-            {
-                "run": {
-                    "name": "Download NLTK files",
-                    "command": """python -c "import nltk; nltk.download('punkt', quiet=True)" """,
-                }
-                if "example" in self.name
-                else "echo Skipping"
-            },
             {
                 "run": {
                     "name": "Show installed libraries and their size",
@@ -310,11 +299,7 @@ def to_dict(self):
 
     @property
     def job_name(self):
-        return (
-            self.name
-            if ("examples" in self.name or "pipeline" in self.name or "pr_documentation" in self.name)
-            else f"tests_{self.name}"
-        )
+        return self.name if ("pipeline" in self.name or "pr_documentation" in self.name) else f"tests_{self.name}"
 
 
 # JOBS
@@ -361,16 +346,6 @@ def job_name(self):
     docker_image=[{"image": "huggingface/transformers-custom-tokenizers"}],
 )
 
-examples_torch_job = CircleCIJob(
-    "examples_torch",
-    disabled=True,  # examples-torch docker image is too large for the large runner
-    additional_env={"OMP_NUM_THREADS": 8},
-    docker_image=[{"image": "huggingface/transformers-examples-torch"}],
-    # TODO @ArthurZucker remove this once docker is easier to build
-    install_steps=["uv pip install . && uv pip install -r examples/pytorch/_tests_requirements.txt"],
-    pytest_num_workers=4,
-)
-
 exotic_models_job = CircleCIJob(
     "exotic_models",
     docker_image=[{"image": "huggingface/transformers-exotic-models"}],
@@ -454,15 +429,14 @@ def job_name(self):
 )
 
 REGULAR_TESTS = [torch_job, tokenization_job, processor_job, generate_job, non_model_job]  # fmt: skip
-EXAMPLES_TESTS = [examples_torch_job]
 PIPELINE_TESTS = [pipelines_torch_job]
 REPO_UTIL_TESTS = [repo_utils_job]
 DOC_TESTS = [doc_test_job]
 TRAINING_CI_TESTS = [training_ci_job]
 TENSOR_PARALLEL_CI_TESTS = [tensor_parallel_ci_job]
 FSDP_CI_TESTS = [fsdp_ci_job]
 PEFT_INTEGRATION_TESTS = [peft_integration_job]
-ALL_TESTS = REGULAR_TESTS + EXAMPLES_TESTS + PIPELINE_TESTS + REPO_UTIL_TESTS + DOC_TESTS + [custom_tokenizers_job] + [exotic_models_job] + TRAINING_CI_TESTS + TENSOR_PARALLEL_CI_TESTS + FSDP_CI_TESTS + PEFT_INTEGRATION_TESTS  # fmt: skip
+ALL_TESTS = REGULAR_TESTS + PIPELINE_TESTS + REPO_UTIL_TESTS + DOC_TESTS + [custom_tokenizers_job] + [exotic_models_job] + TRAINING_CI_TESTS + TENSOR_PARALLEL_CI_TESTS + FSDP_CI_TESTS + PEFT_INTEGRATION_TESTS  # fmt: skip
 
 
 def create_circleci_config(folder=None):

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -79,24 +79,6 @@ body:
 
       placeholder: "@Username ..."
 
-  - type: checkboxes
-    id: information-scripts-examples
-    attributes:
-      label: Information
-      description: 'The problem arises when using:'
-      options:
-        - label: "The official example scripts"
-        - label: "My own modified scripts"
-
-  - type: checkboxes
-    id: information-tasks
-    attributes:
-      label: Tasks
-      description: "The tasks I am working on are:"
-      options:
-        - label: "An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)"
-        - label: "My own task or dataset (give details below)"
-
   - type: textarea
     id: reproduction
     validations:

.github/ISSUE_TEMPLATE/migration.yml

@@ -12,24 +12,6 @@ body:
     validations:
       required: true
 
-  - type: checkboxes
-    id: information-scripts-examples
-    attributes:
-      label: Information
-      description: 'The problem arises when using:'
-      options:
-        - label: "The official example scripts"
-        - label: "My own modified scripts"
-
-  - type: checkboxes
-    id: information-tasks
-    attributes:
-      label: Tasks
-      description: "The tasks I am working on are:"
-      options:
-        - label: "An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)"
-        - label: "My own task or dataset (give details below)"
-
   - type: textarea
     id: reproduction
     validations:
@@ -68,5 +50,3 @@ body:
  ([pytorch-transformers](https://github.com/huggingface/transformers#migrating-from-pytorch-transformers-to-transformers);
   [pytorch-pretrained-bert](https://github.com/huggingface/transformers#migrating-from-pytorch-pretrained-bert-to-transformers))"
           required: true
-        - label: "I checked if a related official extension example runs on my machine."
-          required: true

.github/workflows/build-ci-docker-images.yml

@@ -31,7 +31,7 @@ jobs:
 
     strategy:
       matrix:
-        file: ["quality", "consistency", "custom-tokenizers", "torch-light", "exotic-models", "examples-torch"]
+        file: ["quality", "consistency", "custom-tokenizers", "torch-light", "exotic-models"]
     continue-on-error: true
 
     steps:

.github/workflows/self-scheduled-amd-mi250-caller.yml

@@ -37,18 +37,6 @@ jobs:
       report_repo_id: optimum-amd/transformers_daily_ci
     secrets: inherit
 
-  example-ci:
-    name: Example CI
-    uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@63657f571a92cc9759159442936061c51d6d9ae4 # main
-    with:
-      job: run_examples_gpu
-      slack_report_channel: "#transformers-ci-daily-amd"
-      runner: mi250
-      docker: huggingface/transformers-pytorch-amd-gpu
-      ci_event: Scheduled CI (AMD) - mi250
-      report_repo_id: optimum-amd/transformers_daily_ci
-    secrets: inherit
-
   deepspeed-ci:
     name: DeepSpeed CI
     uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@63657f571a92cc9759159442936061c51d6d9ae4 # main

.github/workflows/self-scheduled-amd-mi300-caller.yml

@@ -86,20 +86,6 @@ jobs:
       commit_sha: ${{ github.event.workflow_run.head_sha || github.sha }}
     secrets: inherit
 
-  example-ci:
-    name: Example CI
-    uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled_arc_scale_set.yaml@main
-    with:
-      job: run_examples_gpu
-      slack_report_channel: "#amd-hf-ci"
-      runner_group: amd-mi300
-      docker: huggingface/transformers-pytorch-amd-gpu
-      ci_event: Scheduled CI (AMD) - mi300
-      report_repo_id: optimum-amd/transformers_daily_ci
-      env_file: /etc/podinfo/gha-gpu-isolation-settings
-      commit_sha: ${{ github.event.workflow_run.head_sha || github.sha }}
-    secrets: inherit
-
   deepspeed-ci:
     name: DeepSpeed CI
     uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled_arc_scale_set.yaml@main

.github/workflows/self-scheduled-amd-mi355-caller.yml

@@ -41,18 +41,6 @@ jobs:
       report_repo_id: hf-transformers-bot/transformers-ci-dummy
     secrets: inherit
 
-  example-ci:
-    name: Example CI
-    uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled_arc_scale_set.yaml@50acccfe9afb8927b9b74ed7e750f2b0d3991b62 # main
-    with:
-      job: run_examples_gpu
-      slack_report_channel: "#amd-hf-ci"
-      runner_group: hfc-amd-mi355
-      docker: huggingface/transformers-pytorch-amd-gpu
-      ci_event: Scheduled CI (AMD) - mi355
-      report_repo_id: hf-transformers-bot/transformers-ci-dummy
-    secrets: inherit
-
   deepspeed-ci:
     name: DeepSpeed CI
     uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled_arc_scale_set.yaml@50acccfe9afb8927b9b74ed7e750f2b0d3991b62 # main

.github/workflows/self-scheduled-caller.yml

@@ -76,18 +76,6 @@ jobs:
       commit_sha: ${{ github.sha }}
     secrets: inherit
 
-  example-ci:
-    name: Example CI
-    uses: huggingface/transformers-ci/.github/workflows/daily-ci_reusable.yml@main
-    with:
-      job: run_examples_gpu
-      slack_report_channel: "#transformers-ci-daily-examples"
-      docker: huggingface/transformers-all-latest-gpu
-      ci_event: Daily CI
-      report_repo_id: hf-internal-testing/transformers_daily_ci
-      commit_sha: ${{ github.sha }}
-    secrets: inherit
-
   trainer-fsdp-ci:
     name: Trainer/FSDP CI
     uses: huggingface/transformers-ci/.github/workflows/daily-ci_reusable.yml@main

.github/workflows/self-scheduled-intel-gaudi.yml

@@ -183,81 +183,6 @@ jobs:
           name: ${{ env.machine_type }}_run_pipelines_torch_gpu_test_reports
           path: reports/${{ env.machine_type }}_run_pipelines_torch_gpu_test_reports
 
-  run_examples_gpu:
-    permissions:
-      contents: read
-    if: ${{ inputs.job == 'run_examples_gpu' }}
-    name: Examples directory
-    strategy:
-      fail-fast: false
-      matrix:
-        machine_type: [1gaudi]
-    runs-on:
-      group: ${{ inputs.runner_scale_set }}-${{ matrix.machine_type }}
-    container:
-      image: vault.habana.ai/gaudi-docker/1.21.1/ubuntu22.04/habanalabs/pytorch-installer-2.6.0:latest
-      options: --runtime=habana
-        -v /mnt/cache/.cache/huggingface:/mnt/cache/.cache/huggingface
-        --env OMPI_MCA_btl_vader_single_copy_mechanism=none
-        --env HABANA_VISIBLE_DEVICES
-        --env HABANA_VISIBLE_MODULES
-        --cap-add=sys_nice
-        --shm-size=64G
-    steps:
-      - name: Checkout
-        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
-        with:
-          fetch-depth: 0
-          persist-credentials: false
-
-      - name: Install dependencies
-        run: |
-          pip install -e .[testing,torch] "numpy<2.0.0" scipy scikit-learn librosa soundfile
-
-      - name: HL-SMI
-        run: |
-          hl-smi
-          echo "HABANA_VISIBLE_DEVICES=${HABANA_VISIBLE_DEVICES}"
-          echo "HABANA_VISIBLE_MODULES=${HABANA_VISIBLE_MODULES}"
-
-      - name: Environment
-        run: |
-          python3 utils/print_env.py
-
-      - name: Show installed libraries and their versions
-        run: |
-          pip freeze
-
-      - name: Set `machine_type` for report and artifact names
-        shell: bash
-        run: |
-          if [ "${{ matrix.machine_type }}" = "1gaudi" ]; then
-            machine_type=single-gpu
-          elif [ "${{ matrix.machine_type }}" = "2gaudi" ]; then
-            machine_type=multi-gpu
-          else
-            machine_type=${{ matrix.machine_type }}
-          fi
-          echo "machine_type=$machine_type" >> $GITHUB_ENV
-
-      - name: Run examples tests on Intel Gaudi
-        run: |
-          pip install -r examples/pytorch/_tests_requirements.txt
-          python3 -m pytest -v --make-reports="${machine_type}_run_examples_gpu_test_reports" examples/pytorch -m "not not_device_test"
-
-      - name: Failure short reports
-        if: ${{ failure() }}
-        continue-on-error: true
-        run: |
-          cat "reports/${machine_type}_run_examples_gpu_test_reports/failures_short.txt"
-
-      - name: "Test suite reports artifacts: ${{ env.machine_type }}_run_examples_gpu_test_reports"
-        if: ${{ always() }}
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
-        with:
-          name: ${{ env.machine_type }}_run_examples_gpu_test_reports
-          path: reports/${{ env.machine_type }}_run_examples_gpu_test_reports
-
   run_torch_cuda_extensions_gpu:
     permissions:
       contents: read
@@ -318,7 +243,7 @@ jobs:
 
       - name: Run all deepspeed tests on intel Gaudi
         run: |
-          python3 -m pytest -v --make-reports="${machine_type}_run_torch_cuda_extensions_gpu_test_reports" tests/deepspeed -m "not not_device_test"
+          python3 -m pytest -v --make-reports="${machine_type}_run_torch_cuda_extensions_gpu_test_reports" tests/trainer/distributed/test_trainer_distributed_deepspeed.py -m "not not_device_test"
 
       - name: Failure short reports
         if: ${{ failure() }}
@@ -427,7 +352,6 @@ jobs:
       [
         setup,
         run_models_gpu,
-        run_examples_gpu,
         run_torch_cuda_extensions_gpu,
         run_pipelines_torch_gpu,
         run_trainer_and_fsdp_gpu,

.github/workflows/self-scheduled-intel-gaudi3-caller.yml

@@ -34,18 +34,6 @@ jobs:
 
     secrets: inherit
 
-  example-ci:
-    name: Example CI
-    uses: ./.github/workflows/self-scheduled-intel-gaudi.yml
-    with:
-      job: run_examples_gpu
-      ci_event: Scheduled CI (Intel) - Gaudi3
-      runner_scale_set: itac-bm-emr-gaudi3-dell
-      slack_report_channel: "#transformers-ci-daily-intel-gaudi3"
-      report_repo_id: optimum-intel/transformers_daily_ci_intel_gaudi3
-
-    secrets: inherit
-
   deepspeed-ci:
     name: DeepSpeed CI
     uses: ./.github/workflows/self-scheduled-intel-gaudi.yml

Makefile

@@ -1,7 +1,7 @@
 # make sure to test the local checkout in scripts and not the pre-installed one (don't use quotes!)
 export PYTHONPATH = src
 
-.PHONY: style typing check-code-quality check-repository-consistency check-repo fix-repo test test-examples benchmark codex claude clean-ai
+.PHONY: style typing check-code-quality check-repository-consistency check-repo fix-repo test benchmark codex claude clean-ai
 
 
 # Checker lists. The two CI jobs (CircleCI runs `make check-code-quality` and
@@ -66,10 +66,6 @@ fix-repo:
 test:
 	python -m pytest -p random_order -n auto --dist=loadfile -s -v --random-order-bucket=module ./tests/
 
-# Run tests for examples, requires pytest-random-order
-test-examples:
-	python -m pytest -p random_order -n auto --dist=loadfile -s -v --random-order-bucket=module ./examples/pytorch/
-
 # Run benchmark
 benchmark:
 	python3 benchmark/benchmark.py --config-dir benchmark/config --config-name generation --commit=diff backend.model=google/gemma-2b backend.cache_implementation=null,static backend.torch_compile=false,true --multirun

README.md

@@ -245,7 +245,6 @@ pipeline(
 
 - This library is not a modular toolbox of building blocks for neural nets. The code in the model files is not refactored with additional abstractions on purpose, so that researchers can quickly iterate on each of the models without diving into additional abstractions/files.
 - The training API is optimized to work with PyTorch models provided by Transformers. For generic machine learning loops, you should use another library like [Accelerate](https://huggingface.co/docs/accelerate).
-- The [example scripts](https://github.com/huggingface/transformers/tree/main/examples) are only *examples*. They may not necessarily work out-of-the-box on your specific use case and you'll need to adapt the code for it to work.
 
 ## 100 projects using Transformers
 

docker/docker-bake.hcl

@@ -32,7 +32,7 @@ target "ci-base" {
 target "ci-image" {
   name       = image
   matrix     = {
-    image = ["quality", "consistency", "custom-tokenizers", "torch-light", "exotic-models", "examples-torch", "pipeline-torch"]
+    image = ["quality", "consistency", "custom-tokenizers", "torch-light", "exotic-models", "pipeline-torch"]
   }
   context    = "docker"
   dockerfile = "${image}.dockerfile"