diff --git a/.github/workflows/test-integrations-data-processing.yml b/.github/workflows/test-integrations-data-processing.yml
index 28c788d69a..b9f1b3fdcb 100644
--- a/.github/workflows/test-integrations-data-processing.yml
+++ b/.github/workflows/test-integrations-data-processing.yml
@@ -70,6 +70,10 @@ jobs:
         run: |
           set -x # print commands that are executed
           ./scripts/runtox.sh "py${{ matrix.python-version }}-openai-latest" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
+      - name: Test huggingface_hub latest
+        run: |
+          set -x # print commands that are executed
+          ./scripts/runtox.sh "py${{ matrix.python-version }}-huggingface_hub-latest" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
       - name: Test rq latest
         run: |
           set -x # print commands that are executed
@@ -134,6 +138,10 @@ jobs:
         run: |
           set -x # print commands that are executed
           ./scripts/runtox.sh --exclude-latest "py${{ matrix.python-version }}-openai" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
+      - name: Test huggingface_hub pinned
+        run: |
+          set -x # print commands that are executed
+          ./scripts/runtox.sh --exclude-latest "py${{ matrix.python-version }}-huggingface_hub" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
       - name: Test rq pinned
         run: |
           set -x # print commands that are executed
diff --git a/mypy.ini b/mypy.ini
index 0d8a60b64c..4f143ede97 100644
--- a/mypy.ini
+++ b/mypy.ini
@@ -73,6 +73,8 @@ ignore_missing_imports = True
 ignore_missing_imports = True
 [mypy-openai.*]
 ignore_missing_imports = True
+[mypy-huggingface_hub.*]
+ignore_missing_imports = True
 [mypy-arq.*]
 ignore_missing_imports = True
 [mypy-grpc.*]
diff --git a/scripts/split-tox-gh-actions/split-tox-gh-actions.py b/scripts/split-tox-gh-actions/split-tox-gh-actions.py
index 53fa55d909..5d5f423857 100755
--- a/scripts/split-tox-gh-actions/split-tox-gh-actions.py
+++ b/scripts/split-tox-gh-actions/split-tox-gh-actions.py
@@ -73,6 +73,7 @@
         "huey",
         "langchain",
         "openai",
+        "huggingface_hub",
         "rq",
     ],
     "Databases": [
diff --git a/sentry_sdk/consts.py b/sentry_sdk/consts.py
index 3ffa384e04..a83fde9f1b 100644
--- a/sentry_sdk/consts.py
+++ b/sentry_sdk/consts.py
@@ -325,6 +325,9 @@ class OP:
     MIDDLEWARE_STARLITE_SEND = "middleware.starlite.send"
     OPENAI_CHAT_COMPLETIONS_CREATE = "ai.chat_completions.create.openai"
     OPENAI_EMBEDDINGS_CREATE = "ai.embeddings.create.openai"
+    HUGGINGFACE_HUB_CHAT_COMPLETIONS_CREATE = (
+        "ai.chat_completions.create.huggingface_hub"
+    )
     LANGCHAIN_PIPELINE = "ai.pipeline.langchain"
     LANGCHAIN_RUN = "ai.run.langchain"
     LANGCHAIN_TOOL = "ai.tool.langchain"
diff --git a/sentry_sdk/integrations/__init__.py b/sentry_sdk/integrations/__init__.py
index f692e88294..fffd573491 100644
--- a/sentry_sdk/integrations/__init__.py
+++ b/sentry_sdk/integrations/__init__.py
@@ -85,6 +85,7 @@ def iter_default_integrations(with_auto_enabling_integrations):
     "sentry_sdk.integrations.graphene.GrapheneIntegration",
     "sentry_sdk.integrations.httpx.HttpxIntegration",
     "sentry_sdk.integrations.huey.HueyIntegration",
+    "sentry_sdk.integrations.huggingface_hub.HuggingfaceHubIntegration",
     "sentry_sdk.integrations.langchain.LangchainIntegration",
     "sentry_sdk.integrations.loguru.LoguruIntegration",
     "sentry_sdk.integrations.openai.OpenAIIntegration",
diff --git a/sentry_sdk/integrations/huggingface_hub.py b/sentry_sdk/integrations/huggingface_hub.py
new file mode 100644
index 0000000000..8e5f0e7339
--- /dev/null
+++ b/sentry_sdk/integrations/huggingface_hub.py
@@ -0,0 +1,173 @@
+from functools import wraps
+
+from sentry_sdk import consts
+from sentry_sdk.ai.monitoring import record_token_usage
+from sentry_sdk.ai.utils import set_data_normalized
+from sentry_sdk.consts import SPANDATA
+
+from typing import Any, Iterable, Callable
+
+import sentry_sdk
+from sentry_sdk.scope import should_send_default_pii
+from sentry_sdk.integrations import DidNotEnable, Integration
+from sentry_sdk.utils import (
+    capture_internal_exceptions,
+    event_from_exception,
+    ensure_integration_enabled,
+)
+
+try:
+    import huggingface_hub.inference._client
+
+    from huggingface_hub import ChatCompletionStreamOutput, TextGenerationOutput
+except ImportError:
+    raise DidNotEnable("Huggingface not installed")
+
+
+class HuggingfaceHubIntegration(Integration):
+    identifier = "huggingface_hub"
+
+    def __init__(self, include_prompts=True):
+        # type: (HuggingfaceHubIntegration, bool) -> None
+        self.include_prompts = include_prompts
+
+    @staticmethod
+    def setup_once():
+        # type: () -> None
+        huggingface_hub.inference._client.InferenceClient.text_generation = (
+            _wrap_text_generation(
+                huggingface_hub.inference._client.InferenceClient.text_generation
+            )
+        )
+
+
+def _capture_exception(exc):
+    # type: (Any) -> None
+    event, hint = event_from_exception(
+        exc,
+        client_options=sentry_sdk.get_client().options,
+        mechanism={"type": "huggingface_hub", "handled": False},
+    )
+    sentry_sdk.capture_event(event, hint=hint)
+
+
+def _wrap_text_generation(f):
+    # type: (Callable[..., Any]) -> Callable[..., Any]
+    @wraps(f)
+    @ensure_integration_enabled(HuggingfaceHubIntegration, f)
+    def new_text_generation(*args, **kwargs):
+        # type: (*Any, **Any) -> Any
+        if "prompt" in kwargs:
+            prompt = kwargs["prompt"]
+        elif len(args) >= 2:
+            kwargs["prompt"] = args[1]
+            prompt = kwargs["prompt"]
+            args = (args[0],) + args[2:]
+        else:
+            # invalid call, let it return error
+            return f(*args, **kwargs)
+
+        model = kwargs.get("model")
+        streaming = kwargs.get("stream")
+
+        span = sentry_sdk.start_span(
+            op=consts.OP.HUGGINGFACE_HUB_CHAT_COMPLETIONS_CREATE,
+            description="Text Generation",
+        )
+        span.__enter__()
+        try:
+            res = f(*args, **kwargs)
+        except Exception as e:
+            _capture_exception(e)
+            span.__exit__(None, None, None)
+            raise e from None
+
+        integration = sentry_sdk.get_client().get_integration(HuggingfaceHubIntegration)
+
+        with capture_internal_exceptions():
+            if should_send_default_pii() and integration.include_prompts:
+                set_data_normalized(span, SPANDATA.AI_INPUT_MESSAGES, prompt)
+
+            set_data_normalized(span, SPANDATA.AI_MODEL_ID, model)
+            set_data_normalized(span, SPANDATA.AI_STREAMING, streaming)
+
+            if isinstance(res, str):
+                if should_send_default_pii() and integration.include_prompts:
+                    set_data_normalized(
+                        span,
+                        "ai.responses",
+                        [res],
+                    )
+                span.__exit__(None, None, None)
+                return res
+
+            if isinstance(res, TextGenerationOutput):
+                if should_send_default_pii() and integration.include_prompts:
+                    set_data_normalized(
+                        span,
+                        "ai.responses",
+                        [res.generated_text],
+                    )
+                if res.details is not None and res.details.generated_tokens > 0:
+                    record_token_usage(span, total_tokens=res.details.generated_tokens)
+                span.__exit__(None, None, None)
+                return res
+
+            if not isinstance(res, Iterable):
+                # we only know how to deal with strings and iterables, ignore
+                set_data_normalized(span, "unknown_response", True)
+                span.__exit__(None, None, None)
+                return res
+
+            if kwargs.get("details", False):
+                # res is Iterable[TextGenerationStreamOutput]
+                def new_details_iterator():
+                    # type: () -> Iterable[ChatCompletionStreamOutput]
+                    with capture_internal_exceptions():
+                        tokens_used = 0
+                        data_buf: list[str] = []
+                        for x in res:
+                            if hasattr(x, "token") and hasattr(x.token, "text"):
+                                data_buf.append(x.token.text)
+                            if hasattr(x, "details") and hasattr(
+                                x.details, "generated_tokens"
+                            ):
+                                tokens_used = x.details.generated_tokens
+                            yield x
+                        if (
+                            len(data_buf) > 0
+                            and should_send_default_pii()
+                            and integration.include_prompts
+                        ):
+                            set_data_normalized(
+                                span, SPANDATA.AI_RESPONSES, "".join(data_buf)
+                            )
+                        if tokens_used > 0:
+                            record_token_usage(span, total_tokens=tokens_used)
+                    span.__exit__(None, None, None)
+
+                return new_details_iterator()
+            else:
+                # res is Iterable[str]
+
+                def new_iterator():
+                    # type: () -> Iterable[str]
+                    data_buf: list[str] = []
+                    with capture_internal_exceptions():
+                        for s in res:
+                            if isinstance(s, str):
+                                data_buf.append(s)
+                            yield s
+                        if (
+                            len(data_buf) > 0
+                            and should_send_default_pii()
+                            and integration.include_prompts
+                        ):
+                            set_data_normalized(
+                                span, SPANDATA.AI_RESPONSES, "".join(data_buf)
+                            )
+                        span.__exit__(None, None, None)
+
+                return new_iterator()
+
+    return new_text_generation
diff --git a/sentry_sdk/integrations/langchain.py b/sentry_sdk/integrations/langchain.py
index 35e955b958..c559870a86 100644
--- a/sentry_sdk/integrations/langchain.py
+++ b/sentry_sdk/integrations/langchain.py
@@ -63,7 +63,7 @@ def count_tokens(s):
 
 # To avoid double collecting tokens, we do *not* measure
 # token counts for models for which we have an explicit integration
-NO_COLLECT_TOKEN_MODELS = ["openai-chat"]
+NO_COLLECT_TOKEN_MODELS = ["openai-chat"]  # TODO add huggingface and anthropic
 
 
 class LangchainIntegration(Integration):
diff --git a/setup.py b/setup.py
index e10fe624e1..39934c8aae 100644
--- a/setup.py
+++ b/setup.py
@@ -60,6 +60,7 @@ def get_file_text(file_name):
         "grpcio": ["grpcio>=1.21.1"],
         "httpx": ["httpx>=0.16.0"],
         "huey": ["huey>=2"],
+        "huggingface_hub": ["huggingface_hub>=0.22"],
         "langchain": ["langchain>=0.0.210"],
         "loguru": ["loguru>=0.5"],
         "openai": ["openai>=1.0.0", "tiktoken>=0.3.0"],
diff --git a/tests/integrations/huggingface_hub/__init__.py b/tests/integrations/huggingface_hub/__init__.py
new file mode 100644
index 0000000000..fe1fa0af50
--- /dev/null
+++ b/tests/integrations/huggingface_hub/__init__.py
@@ -0,0 +1,3 @@
+import pytest
+
+pytest.importorskip("huggingface_hub")
diff --git a/tests/integrations/huggingface_hub/test_huggingface_hub.py b/tests/integrations/huggingface_hub/test_huggingface_hub.py
new file mode 100644
index 0000000000..062bd4fb31
--- /dev/null
+++ b/tests/integrations/huggingface_hub/test_huggingface_hub.py
@@ -0,0 +1,163 @@
+import itertools
+import json
+
+import pytest
+from huggingface_hub import (
+    InferenceClient,
+    TextGenerationOutput,
+    TextGenerationOutputDetails,
+    TextGenerationStreamOutput,
+    TextGenerationOutputToken,
+    TextGenerationStreamDetails,
+)
+from huggingface_hub.errors import OverloadedError
+
+from sentry_sdk import start_transaction
+from sentry_sdk.integrations.huggingface_hub import HuggingfaceHubIntegration
+
+from unittest import mock  # python 3.3 and above
+
+
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts, details_arg",
+    itertools.product([True, False], repeat=3),
+)
+def test_nonstreaming_chat_completion(
+    sentry_init, capture_events, send_default_pii, include_prompts, details_arg
+):
+    sentry_init(
+        integrations=[HuggingfaceHubIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    client = InferenceClient("some-model")
+    if details_arg:
+        client.post = mock.Mock(
+            return_value=json.dumps(
+                [
+                    TextGenerationOutput(
+                        generated_text="the model response",
+                        details=TextGenerationOutputDetails(
+                            finish_reason="TextGenerationFinishReason",
+                            generated_tokens=10,
+                            prefill=[],
+                            tokens=[],  # not needed for integration
+                        ),
+                    )
+                ]
+            ).encode("utf-8")
+        )
+    else:
+        client.post = mock.Mock(
+            return_value=b'[{"generated_text": "the model response"}]'
+        )
+    with start_transaction(name="huggingface_hub tx"):
+        response = client.text_generation(
+            prompt="hello",
+            details=details_arg,
+            stream=False,
+        )
+    if details_arg:
+        assert response.generated_text == "the model response"
+    else:
+        assert response == "the model response"
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    span = tx["spans"][0]
+    assert span["op"] == "ai.chat_completions.create.huggingface_hub"
+
+    if send_default_pii and include_prompts:
+        assert "hello" in span["data"]["ai.input_messages"]
+        assert "the model response" in span["data"]["ai.responses"]
+    else:
+        assert "ai.input_messages" not in span["data"]
+        assert "ai.responses" not in span["data"]
+
+    if details_arg:
+        assert span["measurements"]["ai_total_tokens_used"]["value"] == 10
+
+
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts, details_arg",
+    itertools.product([True, False], repeat=3),
+)
+def test_streaming_chat_completion(
+    sentry_init, capture_events, send_default_pii, include_prompts, details_arg
+):
+    sentry_init(
+        integrations=[HuggingfaceHubIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    client = InferenceClient("some-model")
+    client.post = mock.Mock(
+        return_value=[
+            b"data:"
+            + json.dumps(
+                TextGenerationStreamOutput(
+                    token=TextGenerationOutputToken(
+                        id=1, special=False, text="the model "
+                    ),
+                ),
+            ).encode("utf-8"),
+            b"data:"
+            + json.dumps(
+                TextGenerationStreamOutput(
+                    token=TextGenerationOutputToken(
+                        id=2, special=False, text="response"
+                    ),
+                    details=TextGenerationStreamDetails(
+                        finish_reason="length",
+                        generated_tokens=10,
+                        seed=0,
+                    ),
+                )
+            ).encode("utf-8"),
+        ]
+    )
+    with start_transaction(name="huggingface_hub tx"):
+        response = list(
+            client.text_generation(
+                prompt="hello",
+                details=details_arg,
+                stream=True,
+            )
+        )
+    assert len(response) == 2
+    print(response)
+    if details_arg:
+        assert response[0].token.text + response[1].token.text == "the model response"
+    else:
+        assert response[0] + response[1] == "the model response"
+
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    span = tx["spans"][0]
+    assert span["op"] == "ai.chat_completions.create.huggingface_hub"
+
+    if send_default_pii and include_prompts:
+        assert "hello" in span["data"]["ai.input_messages"]
+        assert "the model response" in span["data"]["ai.responses"]
+    else:
+        assert "ai.input_messages" not in span["data"]
+        assert "ai.responses" not in span["data"]
+
+    if details_arg:
+        assert span["measurements"]["ai_total_tokens_used"]["value"] == 10
+
+
+def test_bad_chat_completion(sentry_init, capture_events):
+    sentry_init(integrations=[HuggingfaceHubIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    client = InferenceClient("some-model")
+    client.post = mock.Mock(side_effect=OverloadedError("The server is overloaded"))
+    with pytest.raises(OverloadedError):
+        client.text_generation(prompt="hello")
+
+    (event,) = events
+    assert event["level"] == "error"
diff --git a/tox.ini b/tox.ini
index 47651c0faf..f1bc0e7a5e 100644
--- a/tox.ini
+++ b/tox.ini
@@ -144,6 +144,9 @@ envlist =
     {py3.6,py3.11,py3.12}-huey-v{2.0}
     {py3.6,py3.11,py3.12}-huey-latest
 
+    # Huggingface Hub
+    {py3.9,py3.11,py3.12}-huggingface_hub-{v0.22,latest}
+
     # Langchain
     {py3.9,py3.11,py3.12}-langchain-0.1
     {py3.9,py3.11,py3.12}-langchain-latest
@@ -446,6 +449,10 @@ deps =
     huey-v2.0: huey~=2.0.0
     huey-latest: huey
 
+    # Huggingface Hub
+    huggingface_hub-v0.22: huggingface_hub~=0.22.2
+    huggingface_hub-latest: huggingface_hub
+
     # Langchain
     langchain: openai~=1.0.0
     langchain-0.1: langchain~=0.1.11
@@ -622,6 +629,7 @@ setenv =
     graphene: TESTPATH=tests/integrations/graphene
     httpx: TESTPATH=tests/integrations/httpx
     huey: TESTPATH=tests/integrations/huey
+    huggingface_hub: TESTPATH=tests/integrations/huggingface_hub
     langchain: TESTPATH=tests/integrations/langchain
     loguru: TESTPATH=tests/integrations/loguru
     openai: TESTPATH=tests/integrations/openai