[InferenceClient] flag chat_completion()'s logit_bias as UNUSED (#2724)

* update logit bias doc

* improve unused parameters documentation

Author: hanouticelina

src/huggingface_hub/inference/_client.py

@@ -576,25 +576,20 @@ def chat_completion(
                 The model to use for chat-completion. Can be a model ID hosted on the Hugging Face Hub or a URL to a deployed
                 Inference Endpoint. If not provided, the default recommended model for chat-based text-generation will be used.
                 See https://huggingface.co/tasks/text-generation for more details.
-
                 If `model` is a model ID, it is passed to the server as the `model` parameter. If you want to define a
                 custom URL while setting `model` in the request payload, you must set `base_url` when initializing [`InferenceClient`].
             frequency_penalty (`float`, *optional*):
                 Penalizes new tokens based on their existing frequency
                 in the text so far. Range: [-2.0, 2.0]. Defaults to 0.0.
             logit_bias (`List[float]`, *optional*):
-                Modify the likelihood of specified tokens appearing in the completion. Accepts a JSON object that maps tokens
-                (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically,
-                the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model,
-                but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should
-                result in a ban or exclusive selection of the relevant token. Defaults to None.
+                UNUSED. Currently not implemented in text-generation-inference (TGI). Kept as a parameter for OpenAI compatibility.
             logprobs (`bool`, *optional*):
                 Whether to return log probabilities of the output tokens or not. If true, returns the log
                 probabilities of each output token returned in the content of message.
             max_tokens (`int`, *optional*):
                 Maximum number of tokens allowed in the response. Defaults to 100.
             n (`int`, *optional*):
-                UNUSED.
+                UNUSED. Currently not implemented in text-generation-inference (TGI). Kept as a parameter for OpenAI compatibility.
             presence_penalty (`float`, *optional*):
                 Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the
                 text so far, increasing the model's likelihood to talk about new topics.

src/huggingface_hub/inference/_generated/_async_client.py

@@ -612,25 +612,20 @@ async def chat_completion(
                 The model to use for chat-completion. Can be a model ID hosted on the Hugging Face Hub or a URL to a deployed
                 Inference Endpoint. If not provided, the default recommended model for chat-based text-generation will be used.
                 See https://huggingface.co/tasks/text-generation for more details.
-
                 If `model` is a model ID, it is passed to the server as the `model` parameter. If you want to define a
                 custom URL while setting `model` in the request payload, you must set `base_url` when initializing [`InferenceClient`].
             frequency_penalty (`float`, *optional*):
                 Penalizes new tokens based on their existing frequency
                 in the text so far. Range: [-2.0, 2.0]. Defaults to 0.0.
             logit_bias (`List[float]`, *optional*):
-                Modify the likelihood of specified tokens appearing in the completion. Accepts a JSON object that maps tokens
-                (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically,
-                the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model,
-                but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should
-                result in a ban or exclusive selection of the relevant token. Defaults to None.
+                UNUSED. Currently not implemented in text-generation-inference (TGI). Kept as a parameter for OpenAI compatibility.
             logprobs (`bool`, *optional*):
                 Whether to return log probabilities of the output tokens or not. If true, returns the log
                 probabilities of each output token returned in the content of message.
             max_tokens (`int`, *optional*):
                 Maximum number of tokens allowed in the response. Defaults to 100.
             n (`int`, *optional*):
-                UNUSED.
+                UNUSED. Currently not implemented in text-generation-inference (TGI). Kept as a parameter for OpenAI compatibility.
             presence_penalty (`float`, *optional*):
                 Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the
                 text so far, increasing the model's likelihood to talk about new topics.