small clean up

src/huggingface_hub/inference/_client.py

@@ -263,8 +263,7 @@ def post(
                 "`InferenceClient.post` is deprecated and should not be used directly anymore."
             )
         provider_helper = HFInferenceTask(task or "unknown")
-        mapped_model = provider_helper.map_model(model, provider="hf-inference", task=task)
-        url = provider_helper.build_url(mapped_model)
+        url = provider_helper.build_url(provider_helper.map_model(model))
         headers = provider_helper.prepare_headers(headers=self.headers, api_key=self.token)
         return self._inner_post(
             request_parameters=RequestParameters(

src/huggingface_hub/inference/_common.py

@@ -107,14 +107,6 @@ def prepare_request(
     @abstractmethod
     def get_response(self, response: Union[bytes, Dict]) -> Any: ...
 
-    def map_model(
-        self, model: Optional[str], provider: str, task: Optional[str] = None, conversational: bool = False
-    ) -> str:
-        """Default implementation for mapping model IDs to provider-specific IDs."""
-        if model is None:
-            raise ValueError(f"Please provide a model available on {provider}.")
-        return _get_provider_model_id(model, provider, task, conversational)
-
 
 #### Fetching Inference Providers model mapping
 _PROVIDER_MAPPINGS: Optional[Dict[str, Dict]] = None
@@ -136,17 +128,10 @@ def _fetch_provider_mappings(model: str) -> Dict:
     return provider_mapping
 
 
-def _get_provider_model_id(
-    model: str, provider: str, task: Optional[str] = None, chat_completion: bool = False
-) -> str:
+def _get_provider_model_id(model: str, provider: str, task: str, conversational: bool = False) -> str:
     """
     Map a model ID to a provider-specific ID.
     """
-    if provider == "hf-inference":
-        return model
-
-    if task is None:
-        raise ValueError("task must be specified when using a third-party provider")
 
     global _PROVIDER_MAPPINGS
     if _PROVIDER_MAPPINGS is None:
@@ -159,7 +144,7 @@ def _get_provider_model_id(
         raise ValueError(f"Model {model} is not supported by provider {provider}")
 
     provider_task = provider_mapping.get("task")
-    requested_task = "conversational" if task == "text-generation" and chat_completion else task
+    requested_task = "conversational" if task == "text-generation" and conversational else task
 
     if provider_task != requested_task:
         raise ValueError(

src/huggingface_hub/inference/_generated/_async_client.py

@@ -258,8 +258,7 @@ async def post(
                 "`InferenceClient.post` is deprecated and should not be used directly anymore."
             )
         provider_helper = HFInferenceTask(task or "unknown")
-        mapped_model = provider_helper.map_model(model, provider="hf-inference", task=task)
-        url = provider_helper.build_url(mapped_model)
+        url = provider_helper.build_url(provider_helper.map_model(model))
         headers = provider_helper.prepare_headers(headers=self.headers, api_key=self.token)
         return await self._inner_post(
             request_parameters=RequestParameters(

src/huggingface_hub/inference/_providers/fal_ai.py

@@ -3,7 +3,7 @@
 from typing import Any, Dict, Optional, Union
 
 from huggingface_hub import constants
-from huggingface_hub.inference._common import RequestParameters, TaskProviderHelper, _as_dict
+from huggingface_hub.inference._common import RequestParameters, TaskProviderHelper, _as_dict, _get_provider_model_id
 from huggingface_hub.utils import build_hf_headers, get_session, get_token, logging
 
 
@@ -36,7 +36,7 @@ def prepare_request(
             raise ValueError(
                 "You must provide an api_key to work with fal.ai API or log in with `huggingface-cli login`."
             )
-        mapped_model = self.map_model(model, provider="fal-ai", task=self.task, conversational=conversational)
+        mapped_model = self.map_model(model=model, task=self.task, conversational=conversational)
         headers = {
             **build_hf_headers(token=api_key),
             **headers,
@@ -62,6 +62,17 @@ def prepare_request(
             headers=headers,
         )
 
+    def map_model(
+        self,
+        model: Optional[str],
+        task: str,
+        conversational: bool = False,
+    ) -> str:
+        """Default implementation for mapping model HF model IDs to provider model IDs."""
+        if model is None:
+            raise ValueError("Please provide a HF model ID supported by fal.ai.")
+        return _get_provider_model_id(model, "fal-ai", task, conversational)
+
     @abstractmethod
     def _prepare_payload(self, inputs: Any, parameters: Dict[str, Any]) -> Dict[str, Any]: ...
 

src/huggingface_hub/inference/_providers/hf_inference.py

@@ -80,11 +80,7 @@ def prepare_request(
     ) -> RequestParameters:
         if extra_payload is None:
             extra_payload = {}
-        if model is None:
-            model = get_recommended_model(self.task)
-        else:
-            model = self.map_model(model, provider="hf-inference", task=self.task, conversational=conversational)
-
+        model = self.map_model(model=model)
         url = self.build_url(model)
         data, json = self._prepare_payload(inputs, parameters=parameters, model=model, extra_payload=extra_payload)
         headers = self.prepare_headers(headers=headers, api_key=api_key)
@@ -98,6 +94,12 @@ def prepare_request(
             headers=headers,
         )
 
+    def map_model(
+        self,
+        model: Optional[str],
+    ) -> str:
+        return model if model is not None else get_recommended_model(self.task)
+
     def build_url(self, model: str) -> str:
         # hf-inference provider can handle URLs (e.g. Inference Endpoints or TGI deployment)
         if model.startswith(("http://", "https://")):
@@ -167,7 +169,7 @@ def prepare_request(
         extra_payload: Optional[Dict[str, Any]] = None,
         conversational: bool = False,
     ) -> RequestParameters:
-        mapped_model = self.map_model(model, provider="hf-inference", task=self.task, conversational=conversational)
+        mapped_model = self.map_model(model)
         payload_model = parameters.get("model") or mapped_model
 
         if payload_model is None or payload_model.startswith(("http://", "https://")):

src/huggingface_hub/inference/_providers/replicate.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, Optional, Union
 
 from huggingface_hub import constants
-from huggingface_hub.inference._common import RequestParameters, TaskProviderHelper, _as_dict
+from huggingface_hub.inference._common import RequestParameters, TaskProviderHelper, _as_dict, _get_provider_model_id
 from huggingface_hub.utils import build_hf_headers, get_session, get_token, logging
 
 
@@ -47,7 +47,7 @@ def prepare_request(
             base_url = BASE_URL
             logger.info("Calling Replicate provider directly.")
 
-        mapped_model = self.map_model(model, provider="replicate", task=self.task, conversational=conversational)
+        mapped_model = self.map_model(model=model, task=self.task, conversational=conversational)
         url = _build_url(base_url, mapped_model)
 
         headers = {
@@ -67,6 +67,17 @@ def prepare_request(
             headers=headers,
         )
 
+    def map_model(
+        self,
+        model: Optional[str],
+        task: str,
+        conversational: bool = False,
+    ) -> str:
+        """Default implementation for mapping model HF model IDs to provider model IDs."""
+        if model is None:
+            raise ValueError("Please provide a HF model ID supported by Replicate.")
+        return _get_provider_model_id(model, "replicate", task, conversational)
+
     def _prepare_payload(
         self,
         inputs: Any,

src/huggingface_hub/inference/_providers/sambanova.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, Optional, Union
 
 from huggingface_hub import constants
-from huggingface_hub.inference._common import RequestParameters, TaskProviderHelper
+from huggingface_hub.inference._common import RequestParameters, TaskProviderHelper, _get_provider_model_id
 from huggingface_hub.utils import build_hf_headers, get_token, logging
 
 
@@ -43,7 +43,7 @@ def prepare_request(
             logger.info("Calling Sambanova provider directly.")
         headers = {**build_hf_headers(token=api_key), **headers}
 
-        mapped_model = self.map_model(model, provider="sambanova", task=self.task, conversational=conversational)
+        mapped_model = self.map_model(model=model, task=self.task, conversational=conversational)
         payload = {
             "messages": inputs,
             **{k: v for k, v in parameters.items() if v is not None},
@@ -59,5 +59,16 @@ def prepare_request(
             headers=headers,
         )
 
+    def map_model(
+        self,
+        model: Optional[str],
+        task: str,
+        conversational: bool = False,
+    ) -> str:
+        """Default implementation for mapping model HF model IDs to provider model IDs."""
+        if model is None:
+            raise ValueError("Please provide a HF model ID supported by Sambanova.")
+        return _get_provider_model_id(model, "sambanova", task, conversational)
+
     def get_response(self, response: Union[bytes, Dict]) -> Any:
         return response

src/huggingface_hub/inference/_providers/together.py

@@ -3,7 +3,7 @@
 from typing import Any, Dict, Optional, Union
 
 from huggingface_hub import constants
-from huggingface_hub.inference._common import RequestParameters, TaskProviderHelper, _as_dict
+from huggingface_hub.inference._common import RequestParameters, TaskProviderHelper, _as_dict, _get_provider_model_id
 from huggingface_hub.utils import build_hf_headers, get_token, logging
 
 
@@ -52,7 +52,7 @@ def prepare_request(
         else:
             base_url = BASE_URL
             logger.info("Calling Together provider directly.")
-        mapped_model = self.map_model(model, provider="together", task=self.task, conversational=conversational)
+        mapped_model = self.map_model(model=model, task=self.task, conversational=conversational)
         if "model" in parameters:
             parameters["model"] = mapped_model
         payload = self._prepare_payload(inputs, parameters=parameters)
@@ -66,6 +66,17 @@ def prepare_request(
             headers=headers,
         )
 
+    def map_model(
+        self,
+        model: Optional[str],
+        task: str,
+        conversational: bool = False,
+    ) -> str:
+        """Default implementation for mapping model HF model IDs to provider model IDs."""
+        if model is None:
+            raise ValueError("Please provide a HF model ID supported by Together.")
+        return _get_provider_model_id(model, "together", task, conversational)
+
     def get_response(self, response: Union[bytes, Dict]) -> Any:
         return response