feat(distro): fork off a starter-gpu distribution

docs/source/providers/post_training/index.md

@@ -9,7 +9,9 @@ This section contains documentation for all available providers for the **post_t
 ```{toctree}
 :maxdepth: 1
 
-inline_huggingface
+inline_huggingface-cpu
-inline_torchtune
+inline_huggingface-gpu
+inline_torchtune-cpu
+inline_torchtune-gpu
 remote_nvidia
 ```

docs/source/providers/post_training/inline_huggingface-cpu.md

@@ -0,0 +1,41 @@
+# inline::huggingface-cpu
+
+## Description
+
+HuggingFace-based post-training provider for fine-tuning models using the HuggingFace ecosystem.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `device` | `<class 'str'>` | No | cuda |  |
+| `distributed_backend` | `Literal['fsdp', 'deepspeed'` | No |  |  |
+| `checkpoint_format` | `Literal['full_state', 'huggingface'` | No | huggingface |  |
+| `chat_template` | `<class 'str'>` | No | <|user|>
+{input}
+<|assistant|>
+{output} |  |
+| `model_specific_config` | `<class 'dict'>` | No | {'trust_remote_code': True, 'attn_implementation': 'sdpa'} |  |
+| `max_seq_length` | `<class 'int'>` | No | 2048 |  |
+| `gradient_checkpointing` | `<class 'bool'>` | No | False |  |
+| `save_total_limit` | `<class 'int'>` | No | 3 |  |
+| `logging_steps` | `<class 'int'>` | No | 10 |  |
+| `warmup_ratio` | `<class 'float'>` | No | 0.1 |  |
+| `weight_decay` | `<class 'float'>` | No | 0.01 |  |
+| `dataloader_num_workers` | `<class 'int'>` | No | 4 |  |
+| `dataloader_pin_memory` | `<class 'bool'>` | No | True |  |
+| `dpo_beta` | `<class 'float'>` | No | 0.1 |  |
+| `use_reference_model` | `<class 'bool'>` | No | True |  |
+| `dpo_loss_type` | `Literal['sigmoid', 'hinge', 'ipo', 'kto_pair'` | No | sigmoid |  |
+| `dpo_output_dir` | `<class 'str'>` | No |  |  |
+
+## Sample Configuration
+
+```yaml
+checkpoint_format: huggingface
+distributed_backend: null
+device: cpu
+dpo_output_dir: ~/.llama/dummy/dpo_output
+
+```
+

docs/source/providers/post_training/inline_huggingface-gpu.md

@@ -0,0 +1,41 @@
+# inline::huggingface-gpu
+
+## Description
+
+HuggingFace-based post-training provider for fine-tuning models using the HuggingFace ecosystem.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `device` | `<class 'str'>` | No | cuda |  |
+| `distributed_backend` | `Literal['fsdp', 'deepspeed'` | No |  |  |
+| `checkpoint_format` | `Literal['full_state', 'huggingface'` | No | huggingface |  |
+| `chat_template` | `<class 'str'>` | No | <|user|>
+{input}
+<|assistant|>
+{output} |  |
+| `model_specific_config` | `<class 'dict'>` | No | {'trust_remote_code': True, 'attn_implementation': 'sdpa'} |  |
+| `max_seq_length` | `<class 'int'>` | No | 2048 |  |
+| `gradient_checkpointing` | `<class 'bool'>` | No | False |  |
+| `save_total_limit` | `<class 'int'>` | No | 3 |  |
+| `logging_steps` | `<class 'int'>` | No | 10 |  |
+| `warmup_ratio` | `<class 'float'>` | No | 0.1 |  |
+| `weight_decay` | `<class 'float'>` | No | 0.01 |  |
+| `dataloader_num_workers` | `<class 'int'>` | No | 4 |  |
+| `dataloader_pin_memory` | `<class 'bool'>` | No | True |  |
+| `dpo_beta` | `<class 'float'>` | No | 0.1 |  |
+| `use_reference_model` | `<class 'bool'>` | No | True |  |
+| `dpo_loss_type` | `Literal['sigmoid', 'hinge', 'ipo', 'kto_pair'` | No | sigmoid |  |
+| `dpo_output_dir` | `<class 'str'>` | No |  |  |
+
+## Sample Configuration
+
+```yaml
+checkpoint_format: huggingface
+distributed_backend: null
+device: cpu
+dpo_output_dir: ~/.llama/dummy/dpo_output
+
+```
+

docs/source/providers/post_training/inline_torchtune-cpu.md

@@ -0,0 +1,20 @@
+# inline::torchtune-cpu
+
+## Description
+
+TorchTune-based post-training provider for fine-tuning and optimizing models using Meta's TorchTune framework.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `torch_seed` | `int \| None` | No |  |  |
+| `checkpoint_format` | `Literal['meta', 'huggingface'` | No | meta |  |
+
+## Sample Configuration
+
+```yaml
+checkpoint_format: meta
+
+```
+

docs/source/providers/post_training/inline_torchtune-gpu.md

@@ -0,0 +1,20 @@
+# inline::torchtune-gpu
+
+## Description
+
+TorchTune-based post-training provider for fine-tuning and optimizing models using Meta's TorchTune framework.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `torch_seed` | `int \| None` | No |  |  |
+| `checkpoint_format` | `Literal['meta', 'huggingface'` | No | meta |  |
+
+## Sample Configuration
+
+```yaml
+checkpoint_format: meta
+
+```
+

llama_stack/distributions/ci-tests/build.yaml

@@ -34,7 +34,7 @@ distribution_spec:
     telemetry:
     - provider_type: inline::meta-reference
     post_training:
-    - provider_type: inline::huggingface
+    - provider_type: inline::huggingface-cpu
     eval:
     - provider_type: inline::meta-reference
     datasetio:

llama_stack/distributions/ci-tests/run.yaml

@@ -156,8 +156,8 @@ providers:
       sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ci-tests}/trace_store.db
       otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
   post_training:
-  - provider_id: huggingface
+  - provider_id: huggingface-cpu
-    provider_type: inline::huggingface
+    provider_type: inline::huggingface-cpu
     config:
       checkpoint_format: huggingface
       distributed_backend: null

llama_stack/distributions/starter-gpu/__init__.py

@@ -0,0 +1,7 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from .starter_gpu import get_distribution_template  # noqa: F401

llama_stack/distributions/starter-gpu/build.yaml

@@ -0,0 +1,59 @@
+version: 2
+distribution_spec:
+  description: Quick start template for running Llama Stack with several popular providers.
+    This distribution is intended for GPU-enabled environments.
+  providers:
+    inference:
+    - provider_type: remote::cerebras
+    - provider_type: remote::ollama
+    - provider_type: remote::vllm
+    - provider_type: remote::tgi
+    - provider_type: remote::fireworks
+    - provider_type: remote::together
+    - provider_type: remote::bedrock
+    - provider_type: remote::nvidia
+    - provider_type: remote::openai
+    - provider_type: remote::anthropic
+    - provider_type: remote::gemini
+    - provider_type: remote::vertexai
+    - provider_type: remote::groq
+    - provider_type: remote::sambanova
+    - provider_type: inline::sentence-transformers
+    vector_io:
+    - provider_type: inline::faiss
+    - provider_type: inline::sqlite-vec
+    - provider_type: inline::milvus
+    - provider_type: remote::chromadb
+    - provider_type: remote::pgvector
+    files:
+    - provider_type: inline::localfs
+    safety:
+    - provider_type: inline::llama-guard
+    - provider_type: inline::code-scanner
+    agents:
+    - provider_type: inline::meta-reference
+    telemetry:
+    - provider_type: inline::meta-reference
+    post_training:
+    - provider_type: inline::torchtune-gpu
+    eval:
+    - provider_type: inline::meta-reference
+    datasetio:
+    - provider_type: remote::huggingface
+    - provider_type: inline::localfs
+    scoring:
+    - provider_type: inline::basic
+    - provider_type: inline::llm-as-judge
+    - provider_type: inline::braintrust
+    tool_runtime:
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: inline::rag-runtime
+    - provider_type: remote::model-context-protocol
+    batches:
+    - provider_type: inline::reference
+image_type: venv
+additional_pip_packages:
+- aiosqlite
+- asyncpg
+- sqlalchemy[asyncio]

llama_stack/distributions/starter-gpu/run.yaml

@@ -0,0 +1,238 @@
+version: 2
+image_name: starter-gpu
+apis:
+- agents
+- batches
+- datasetio
+- eval
+- files
+- inference
+- post_training
+- safety
+- scoring
+- telemetry
+- tool_runtime
+- vector_io
+providers:
+  inference:
+  - provider_id: ${env.CEREBRAS_API_KEY:+cerebras}
+    provider_type: remote::cerebras
+    config:
+      base_url: https://api.cerebras.ai
+      api_key: ${env.CEREBRAS_API_KEY:=}
+  - provider_id: ${env.OLLAMA_URL:+ollama}
+    provider_type: remote::ollama
+    config:
+      url: ${env.OLLAMA_URL:=http://localhost:11434}
+  - provider_id: ${env.VLLM_URL:+vllm}
+    provider_type: remote::vllm
+    config:
+      url: ${env.VLLM_URL:=}
+      max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
+      api_token: ${env.VLLM_API_TOKEN:=fake}
+      tls_verify: ${env.VLLM_TLS_VERIFY:=true}
+  - provider_id: ${env.TGI_URL:+tgi}
+    provider_type: remote::tgi
+    config:
+      url: ${env.TGI_URL:=}
+  - provider_id: fireworks
+    provider_type: remote::fireworks
+    config:
+      url: https://api.fireworks.ai/inference/v1
+      api_key: ${env.FIREWORKS_API_KEY:=}
+  - provider_id: together
+    provider_type: remote::together
+    config:
+      url: https://api.together.xyz/v1
+      api_key: ${env.TOGETHER_API_KEY:=}
+  - provider_id: bedrock
+    provider_type: remote::bedrock
+  - provider_id: ${env.NVIDIA_API_KEY:+nvidia}
+    provider_type: remote::nvidia
+    config:
+      url: ${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com}
+      api_key: ${env.NVIDIA_API_KEY:=}
+      append_api_version: ${env.NVIDIA_APPEND_API_VERSION:=True}
+  - provider_id: openai
+    provider_type: remote::openai
+    config:
+      api_key: ${env.OPENAI_API_KEY:=}
+      base_url: ${env.OPENAI_BASE_URL:=https://api.openai.com/v1}
+  - provider_id: anthropic
+    provider_type: remote::anthropic
+    config:
+      api_key: ${env.ANTHROPIC_API_KEY:=}
+  - provider_id: gemini
+    provider_type: remote::gemini
+    config:
+      api_key: ${env.GEMINI_API_KEY:=}
+  - provider_id: ${env.VERTEX_AI_PROJECT:+vertexai}
+    provider_type: remote::vertexai
+    config:
+      project: ${env.VERTEX_AI_PROJECT:=}
+      location: ${env.VERTEX_AI_LOCATION:=us-central1}
+  - provider_id: groq
+    provider_type: remote::groq
+    config:
+      url: https://api.groq.com
+      api_key: ${env.GROQ_API_KEY:=}
+  - provider_id: sambanova
+    provider_type: remote::sambanova
+    config:
+      url: https://api.sambanova.ai/v1
+      api_key: ${env.SAMBANOVA_API_KEY:=}
+  - provider_id: sentence-transformers
+    provider_type: inline::sentence-transformers
+  vector_io:
+  - provider_id: faiss
+    provider_type: inline::faiss
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/faiss_store.db
+  - provider_id: sqlite-vec
+    provider_type: inline::sqlite-vec
+    config:
+      db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec.db
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec_registry.db
+  - provider_id: ${env.MILVUS_URL:+milvus}
+    provider_type: inline::milvus
+    config:
+      db_path: ${env.MILVUS_DB_PATH:=~/.llama/distributions/starter}/milvus.db
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/milvus_registry.db
+  - provider_id: ${env.CHROMADB_URL:+chromadb}
+    provider_type: remote::chromadb
+    config:
+      url: ${env.CHROMADB_URL:=}
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter/}/chroma_remote_registry.db
+  - provider_id: ${env.PGVECTOR_DB:+pgvector}
+    provider_type: remote::pgvector
+    config:
+      host: ${env.PGVECTOR_HOST:=localhost}
+      port: ${env.PGVECTOR_PORT:=5432}
+      db: ${env.PGVECTOR_DB:=}
+      user: ${env.PGVECTOR_USER:=}
+      password: ${env.PGVECTOR_PASSWORD:=}
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/pgvector_registry.db
+  files:
+  - provider_id: meta-reference-files
+    provider_type: inline::localfs
+    config:
+      storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/starter/files}
+      metadata_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/files_metadata.db
+  safety:
+  - provider_id: llama-guard
+    provider_type: inline::llama-guard
+    config:
+      excluded_categories: []
+  - provider_id: code-scanner
+    provider_type: inline::code-scanner
+  agents:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      persistence_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/agents_store.db
+      responses_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/responses_store.db
+  telemetry:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
+      sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
+      sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/trace_store.db
+      otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
+  post_training:
+  - provider_id: torchtune-gpu
+    provider_type: inline::torchtune-gpu
+    config:
+      checkpoint_format: meta
+  eval:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/meta_reference_eval.db
+  datasetio:
+  - provider_id: huggingface
+    provider_type: remote::huggingface
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/huggingface_datasetio.db
+  - provider_id: localfs
+    provider_type: inline::localfs
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/localfs_datasetio.db
+  scoring:
+  - provider_id: basic
+    provider_type: inline::basic
+  - provider_id: llm-as-judge
+    provider_type: inline::llm-as-judge
+  - provider_id: braintrust
+    provider_type: inline::braintrust
+    config:
+      openai_api_key: ${env.OPENAI_API_KEY:=}
+  tool_runtime:
+  - provider_id: brave-search
+    provider_type: remote::brave-search
+    config:
+      api_key: ${env.BRAVE_SEARCH_API_KEY:=}
+      max_results: 3
+  - provider_id: tavily-search
+    provider_type: remote::tavily-search
+    config:
+      api_key: ${env.TAVILY_SEARCH_API_KEY:=}
+      max_results: 3
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
+  batches:
+  - provider_id: reference
+    provider_type: inline::reference
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/batches.db
+metadata_store:
+  type: sqlite
+  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/registry.db
+inference_store:
+  type: sqlite
+  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/inference_store.db
+models: []
+shields:
+- shield_id: llama-guard
+  provider_id: ${env.SAFETY_MODEL:+llama-guard}
+  provider_shield_id: ${env.SAFETY_MODEL:=}
+- shield_id: code-scanner
+  provider_id: ${env.CODE_SCANNER_MODEL:+code-scanner}
+  provider_shield_id: ${env.CODE_SCANNER_MODEL:=}
+vector_dbs: []
+datasets: []
+scoring_fns: []
+benchmarks: []
+tool_groups:
+- toolgroup_id: builtin::websearch
+  provider_id: tavily-search
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
+server:
+  port: 8321

llama_stack/distributions/starter-gpu/starter_gpu.py

@@ -0,0 +1,22 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+
+from llama_stack.distributions.template import BuildProvider, DistributionTemplate
+
+from ..starter.starter import get_distribution_template as get_starter_distribution_template
+
+
+def get_distribution_template() -> DistributionTemplate:
+    template = get_starter_distribution_template()
+    name = "starter-gpu"
+    template.name = name
+    template.description = "Quick start template for running Llama Stack with several popular providers. This distribution is intended for GPU-enabled environments."
+
+    template.providers["post_training"] = [
+        BuildProvider(provider_type="inline::torchtune-gpu"),
+    ]
+    return template

llama_stack/distributions/starter/build.yaml

@@ -1,6 +1,7 @@
 version: 2
 distribution_spec:
-  description: Quick start template for running Llama Stack with several popular providers
+  description: Quick start template for running Llama Stack with several popular providers.
+    This distribution is intended for CPU-only environments.
   providers:
     inference:
     - provider_type: remote::cerebras
@@ -34,7 +35,7 @@ distribution_spec:
     telemetry:
     - provider_type: inline::meta-reference
     post_training:
-    - provider_type: inline::huggingface
+    - provider_type: inline::huggingface-cpu
     eval:
     - provider_type: inline::meta-reference
     datasetio:

llama_stack/distributions/starter/run.yaml

@@ -156,8 +156,8 @@ providers:
       sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/trace_store.db
       otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
   post_training:
-  - provider_id: huggingface
+  - provider_id: huggingface-cpu
-    provider_type: inline::huggingface
+    provider_type: inline::huggingface-cpu
     config:
       checkpoint_format: huggingface
       distributed_backend: null

llama_stack/distributions/starter/starter.py

@@ -120,7 +120,7 @@ def get_distribution_template() -> DistributionTemplate:
         ],
         "agents": [BuildProvider(provider_type="inline::meta-reference")],
         "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
-        "post_training": [BuildProvider(provider_type="inline::huggingface")],
+        "post_training": [BuildProvider(provider_type="inline::huggingface-cpu")],
         "eval": [BuildProvider(provider_type="inline::meta-reference")],
         "datasetio": [
             BuildProvider(provider_type="remote::huggingface"),
@@ -178,7 +178,7 @@ def get_distribution_template() -> DistributionTemplate:
     return DistributionTemplate(
         name=name,
         distro_type="self_hosted",
-        description="Quick start template for running Llama Stack with several popular providers",
+        description="Quick start template for running Llama Stack with several popular providers. This distribution is intended for CPU-only environments.",
         container_image=None,
         template_path=None,
         providers=providers,

llama_stack/providers/registry/post_training.py

@@ -5,15 +5,15 @@
 # the root directory of this source tree.
 
 
+from typing import cast
+
 from llama_stack.providers.datatypes import AdapterSpec, Api, InlineProviderSpec, ProviderSpec, remote_provider_spec
 
-
+# We provide two versions of these providers so that distributions can package the appropriate version of torch.
-def available_providers() -> list[ProviderSpec]:
+# The CPU version is used for distributions that don't have GPU support -- they result in smaller container images.
-    return [
+torchtune_def = dict(
-        InlineProviderSpec(
     api=Api.post_training,
-            provider_type="inline::torchtune",
+    pip_packages=["torchtune==0.5.0", "torchao==0.8.0", "numpy"],
-            pip_packages=["torch", "torchtune==0.5.0", "torchao==0.8.0", "numpy"],
     module="llama_stack.providers.inline.post_training.torchtune",
     config_class="llama_stack.providers.inline.post_training.torchtune.TorchtunePostTrainingConfig",
     api_dependencies=[
@@ -21,11 +21,11 @@ def available_providers() -> list[ProviderSpec]:
         Api.datasets,
     ],
     description="TorchTune-based post-training provider for fine-tuning and optimizing models using Meta's TorchTune framework.",
-        ),
+)
-        InlineProviderSpec(
+
+huggingface_def = dict(
     api=Api.post_training,
-            provider_type="inline::huggingface",
+    pip_packages=["trl", "transformers", "peft", "datasets"],
-            pip_packages=["torch", "trl", "transformers", "peft", "datasets"],
     module="llama_stack.providers.inline.post_training.huggingface",
     config_class="llama_stack.providers.inline.post_training.huggingface.HuggingFacePostTrainingConfig",
     api_dependencies=[
@@ -33,6 +33,46 @@ def available_providers() -> list[ProviderSpec]:
         Api.datasets,
     ],
     description="HuggingFace-based post-training provider for fine-tuning models using the HuggingFace ecosystem.",
+)
+
+
+def available_providers() -> list[ProviderSpec]:
+    return [
+        InlineProviderSpec(
+            **{
+                **torchtune_def,
+                "provider_type": "inline::torchtune-cpu",
+                "pip_packages": (
+                    cast(list[str], torchtune_def["pip_packages"])
+                    + ["torch torchtune==0.5.0 torchao==0.8.0 --index-url https://download.pytorch.org/whl/cpu"]
+                ),
+            },
+        ),
+        InlineProviderSpec(
+            **{
+                **huggingface_def,
+                "provider_type": "inline::huggingface-cpu",
+                "pip_packages": (
+                    cast(list[str], huggingface_def["pip_packages"])
+                    + ["torch --index-url https://download.pytorch.org/whl/cpu"]
+                ),
+            },
+        ),
+        InlineProviderSpec(
+            **{
+                **torchtune_def,
+                "provider_type": "inline::torchtune-gpu",
+                "pip_packages": (
+                    cast(list[str], torchtune_def["pip_packages"]) + ["torch torchtune==0.5.0 torchao==0.8.0"]
+                ),
+            },
+        ),
+        InlineProviderSpec(
+            **{
+                **huggingface_def,
+                "provider_type": "inline::huggingface-gpu",
+                "pip_packages": (cast(list[str], huggingface_def["pip_packages"]) + ["torch"]),
+            },
         ),
         remote_provider_spec(
             api=Api.post_training,