🚨 No more default chat templates (huggingface#31733)

* No more default chat templates

* Add the template to the GPT-SW3 tests since it's not available by default now

* Fix GPT2 test

* Fix Bloom test

* Fix Bloom test

* Remove default templates again

Author: Rocketknight1

docs/source/en/chat_templating.md

@@ -580,7 +580,7 @@ default template for that model class is used instead. Let's take a look at the
 >>> from transformers import AutoTokenizer
 >>> tokenizer = AutoTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
 
->>> tokenizer.default_chat_template
+>>> tokenizer.chat_template
 "{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ '  ' }}{% endif %}{% endfor %}{{ eos_token }}"
 ```
 
@@ -704,23 +704,6 @@ with other names, pass the name of the template you want to the `chat_template`
 We find that this can be a bit confusing for users, though - so if you're writing a template yourself, we recommend
 trying to put it all in a single template where possible!
 
-### What are "default" templates?
-
-Before the introduction of chat templates, chat handling was hardcoded at the model class level. For backwards 
-compatibility, we have retained this class-specific handling as default templates, also set at the class level. If a
-model does not have a chat template set, but there is a default template for its model class, the `TextGenerationPipeline`
-class and methods like `apply_chat_template` will use the class template instead. You can find out what the default
-template for your tokenizer is by checking the `tokenizer.default_chat_template` attribute.
-
-This is something we do purely for backward compatibility reasons, to avoid breaking any existing workflows. Even when
-the class template is appropriate for your model, we strongly recommend overriding the default template by
-setting the `chat_template` attribute explicitly to make it clear to users that your model has been correctly configured
-for chat.
-
-Now that actual chat templates have been adopted more widely, default templates have been deprecated and will be
-removed in a future release. We strongly recommend setting the `chat_template` attribute for any tokenizers that
-still depend on them!
-
 ### What template should I use?
 
 When setting the template for a model that's already been trained for chat, you should ensure that the template

docs/source/es/chat_templating.md

@@ -220,7 +220,7 @@ La plantilla de chat para un modelo se almacena en el atributo `tokenizer.chat_t
 >>> from transformers import AutoTokenizer
 >>> tokenizer = AutoTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
 
->>> tokenizer.default_chat_template
+>>> tokenizer.chat_template
 "{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ '  ' }}{% endif %}{% endfor %}{{ eos_token }}"
 ```
 
@@ -307,12 +307,6 @@ Si estás ajustando finamente un modelo para chat, además de establecer una pla
 
 </Tip>
 
-### ¿Qué son las plantillas "default"?
-
-Antes de la introducción de las plantillas de chat, el manejo del chat estaba codificado en el nivel de la clase del modelo. Por razones de compatibilidad con versiones anteriores, hemos conservado este manejo específico de la clase como plantillas predeterminadas, también establecidas a nivel de clase. Si un modelo no tiene una plantilla de chat establecida, pero hay una plantilla predeterminada para su clase de modelo, la clase `TextGenerationPipeline` y métodos como `apply_chat_template` usarán la plantilla de clase en su lugar. Puedes averiguar cuál es la plantilla predeterminada para tu tokenizador comprobando el atributo `tokenizer.default_chat_template`.
-
-Esto es algo que hacemos puramente por razones de compatibilidad con versiones anteriores, para evitar romper cualquier flujo de trabajo existente. Incluso cuando la plantilla de clase es apropiada para tu modelo, recomendamos encarecidamente anular la plantilla predeterminada estableciendo explícitamente el atributo `chat_template` para dejar claro a los usuarios que tu modelo ha sido configurado correctamente para el chat, y para estar preparados para el futuro en caso de que las plantillas predeterminadas alguna vez se alteren o se eliminen.
-
 ### ¿Qué plantilla debería usar?
 
 Cuando establezcas la plantilla para un modelo que ya ha sido entrenado para chat, debes asegurarte de que la plantilla coincida exactamente con el formato de mensajes que el modelo vio durante el entrenamiento, o de lo contrario es probable que experimentes degradación del rendimiento. Esto es cierto incluso si estás entrenando aún más el modelo; probablemente obtendrás el mejor rendimiento si mantienes constantes los tokens de chat. Esto es muy análogo a la tokenización: generalmente obtienes el mejor rendimiento para la inferencia o el ajuste fino cuando coincides precisamente con la tokenización utilizada durante el entrenamiento.

docs/source/ja/chat_templating.md

@@ -85,7 +85,7 @@ LLM（Language Model）のますます一般的な使用事例の1つは「チ
 >>> from transformers import AutoTokenizer
 >>> tokenizer = AutoTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
 
->>> tokenizer.default_chat_template
+>>> tokenizer.chat_template
 "{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ '  ' }}{% endif %}{% endfor %}{{ eos_token }}"
 ```
 

docs/source/zh/chat_templating.md

@@ -228,7 +228,7 @@ The sun.</s>
 >>> from transformers import AutoTokenizer
 >>> tokenizer = AutoTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
 
->>> tokenizer.default_chat_template
+>>> tokenizer.chat_template
 "{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ '  ' }}{% endif %}{% endfor %}{{ eos_token }}"
 ```
 

src/transformers/models/blenderbot/tokenization_blenderbot.py

@@ -405,17 +405,3 @@ def build_inputs_with_special_tokens(self, token_ids_0: List[int], token_ids_1:
             `List[int]`: list of [input IDs](../glossary#input-ids) with the appropriate special tokens.
         """
         return token_ids_0 + [self.eos_token_id]
-
-    @property
-    def default_chat_template(self):
-        """
-        A very simple chat template that just adds whitespace between messages.
-        """
-        return (
-            "{% for message in messages %}"
-            "{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}"
-            "{{ message['content'] }}"
-            "{% if not loop.last %}{{ '  ' }}{% endif %}"
-            "{% endfor %}"
-            "{{ eos_token }}"
-        )

src/transformers/models/blenderbot/tokenization_blenderbot_fast.py

@@ -287,18 +287,3 @@ def build_inputs_with_special_tokens(self, token_ids_0: List[int], token_ids_1:
             `List[int]`: list of [input IDs](../glossary#input-ids) with the appropriate special tokens.
         """
         return token_ids_0 + [self.eos_token_id]
-
-    @property
-    # Copied from transformers.models.blenderbot.tokenization_blenderbot.BlenderbotTokenizer.default_chat_template
-    def default_chat_template(self):
-        """
-        A very simple chat template that just adds whitespace between messages.
-        """
-        return (
-            "{% for message in messages %}"
-            "{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}"
-            "{{ message['content'] }}"
-            "{% if not loop.last %}{{ '  ' }}{% endif %}"
-            "{% endfor %}"
-            "{{ eos_token }}"
-        )

src/transformers/models/blenderbot_small/tokenization_blenderbot_small.py

@@ -217,18 +217,3 @@ def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] =
                 index += 1
 
         return vocab_file, merge_file
-
-    @property
-    # Copied from transformers.models.blenderbot.tokenization_blenderbot.BlenderbotTokenizer.default_chat_template
-    def default_chat_template(self):
-        """
-        A very simple chat template that just adds whitespace between messages.
-        """
-        return (
-            "{% for message in messages %}"
-            "{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}"
-            "{{ message['content'] }}"
-            "{% if not loop.last %}{{ '  ' }}{% endif %}"
-            "{% endfor %}"
-            "{{ eos_token }}"
-        )

src/transformers/models/blenderbot_small/tokenization_blenderbot_small_fast.py

@@ -98,18 +98,3 @@ def create_token_type_ids_from_sequences(
         if token_ids_1 is None:
             return len(cls + token_ids_0 + sep) * [0]
         return len(cls + token_ids_0 + sep + sep + token_ids_1 + sep) * [0]
-
-    @property
-    # Copied from transformers.models.blenderbot.tokenization_blenderbot.BlenderbotTokenizer.default_chat_template
-    def default_chat_template(self):
-        """
-        A very simple chat template that just adds whitespace between messages.
-        """
-        return (
-            "{% for message in messages %}"
-            "{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}"
-            "{{ message['content'] }}"
-            "{% if not loop.last %}{{ '  ' }}{% endif %}"
-            "{% endfor %}"
-            "{{ eos_token }}"
-        )

src/transformers/models/bloom/tokenization_bloom_fast.py

@@ -147,11 +147,3 @@ def _encode_plus(self, *args, **kwargs) -> BatchEncoding:
     def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] = None) -> Tuple[str]:
         files = self._tokenizer.model.save(save_directory, name=filename_prefix)
         return tuple(files)
-
-    @property
-    # Copied from transformers.models.gpt2.tokenization_gpt2.GPT2Tokenizer.default_chat_template
-    def default_chat_template(self):
-        """
-        A simple chat template that ignores role information and just concatenates messages with EOS tokens.
-        """
-        return "{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}"

src/transformers/models/code_llama/tokenization_code_llama.py

@@ -437,61 +437,6 @@ def create_token_type_ids_from_sequences(
 
         return output
 
-    @property
-    # Copied from transformers.models.llama.tokenization_llama.LlamaTokenizer.default_chat_template
-    def default_chat_template(self):
-        """
-        LLaMA uses [INST] and [/INST] to indicate user messages, and <<SYS>> and <</SYS>> to indicate system messages.
-        Assistant messages do not have special tokens, because LLaMA chat models are generally trained with strict
-        user/assistant/user/assistant message ordering, and so assistant messages can be identified from the ordering
-        rather than needing special tokens. The system message is partly 'embedded' in the first user message, which
-        results in an unusual token ordering when it is present. This template should definitely be changed if you wish
-        to fine-tune a model with more flexible role ordering!
-
-        The output should look something like:
-
-        <bos>[INST] B_SYS SystemPrompt E_SYS Prompt [/INST] Answer <eos><bos>[INST] Prompt [/INST] Answer <eos>
-        <bos>[INST] Prompt [/INST]
-
-        The reference for this chat template is [this code
-        snippet](https://github.com/facebookresearch/llama/blob/556949fdfb72da27c2f4a40b7f0e4cf0b8153a28/llama/generation.py#L320-L362)
-        in the original repository.
-        """
-        template = (
-            "{% if messages[0]['role'] == 'system' %}"
-            "{% set loop_messages = messages[1:] %}"  # Extract system message if it's present
-            "{% set system_message = messages[0]['content'] %}"
-            "{% elif USE_DEFAULT_PROMPT == true and not '<<SYS>>' in messages[0]['content'] %}"
-            "{% set loop_messages = messages %}"  # Or use the default system message if the flag is set
-            "{% set system_message = 'DEFAULT_SYSTEM_MESSAGE' %}"
-            "{% else %}"
-            "{% set loop_messages = messages %}"
-            "{% set system_message = false %}"
-            "{% endif %}"
-            "{% for message in loop_messages %}"  # Loop over all non-system messages
-            "{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}"
-            "{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}"
-            "{% endif %}"
-            "{% if loop.index0 == 0 and system_message != false %}"  # Embed system message in first message
-            "{% set content = '<<SYS>>\\n' + system_message + '\\n<</SYS>>\\n\\n' + message['content'] %}"
-            "{% else %}"
-            "{% set content = message['content'] %}"
-            "{% endif %}"
-            "{% if message['role'] == 'user' %}"  # After all of that, handle messages/roles in a fairly normal way
-            "{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}"
-            "{% elif message['role'] == 'system' %}"
-            "{{ '<<SYS>>\\n' + content.strip() + '\\n<</SYS>>\\n\\n' }}"
-            "{% elif message['role'] == 'assistant' %}"
-            "{{ ' '  + content.strip() + ' ' + eos_token }}"
-            "{% endif %}"
-            "{% endfor %}"
-        )
-        template = template.replace("USE_DEFAULT_PROMPT", "true" if self.use_default_system_prompt else "false")
-        default_message = DEFAULT_SYSTEM_PROMPT.replace("\n", "\\n").replace("'", "\\'")
-        template = template.replace("DEFAULT_SYSTEM_MESSAGE", default_message)
-
-        return template
-
     def __getstate__(self):
         state = self.__dict__.copy()
         state["sp_model"] = None

src/transformers/models/code_llama/tokenization_code_llama_fast.py

@@ -349,61 +349,6 @@ def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] =
 
         return (out_vocab_file,)
 
-    @property
-    # Copied from transformers.models.llama.tokenization_llama.LlamaTokenizer.default_chat_template
-    def default_chat_template(self):
-        """
-        LLaMA uses [INST] and [/INST] to indicate user messages, and <<SYS>> and <</SYS>> to indicate system messages.
-        Assistant messages do not have special tokens, because LLaMA chat models are generally trained with strict
-        user/assistant/user/assistant message ordering, and so assistant messages can be identified from the ordering
-        rather than needing special tokens. The system message is partly 'embedded' in the first user message, which
-        results in an unusual token ordering when it is present. This template should definitely be changed if you wish
-        to fine-tune a model with more flexible role ordering!
-
-        The output should look something like:
-
-        <bos>[INST] B_SYS SystemPrompt E_SYS Prompt [/INST] Answer <eos><bos>[INST] Prompt [/INST] Answer <eos>
-        <bos>[INST] Prompt [/INST]
-
-        The reference for this chat template is [this code
-        snippet](https://github.com/facebookresearch/llama/blob/556949fdfb72da27c2f4a40b7f0e4cf0b8153a28/llama/generation.py#L320-L362)
-        in the original repository.
-        """
-        template = (
-            "{% if messages[0]['role'] == 'system' %}"
-            "{% set loop_messages = messages[1:] %}"  # Extract system message if it's present
-            "{% set system_message = messages[0]['content'] %}"
-            "{% elif USE_DEFAULT_PROMPT == true and not '<<SYS>>' in messages[0]['content'] %}"
-            "{% set loop_messages = messages %}"  # Or use the default system message if the flag is set
-            "{% set system_message = 'DEFAULT_SYSTEM_MESSAGE' %}"
-            "{% else %}"
-            "{% set loop_messages = messages %}"
-            "{% set system_message = false %}"
-            "{% endif %}"
-            "{% for message in loop_messages %}"  # Loop over all non-system messages
-            "{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}"
-            "{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}"
-            "{% endif %}"
-            "{% if loop.index0 == 0 and system_message != false %}"  # Embed system message in first message
-            "{% set content = '<<SYS>>\\n' + system_message + '\\n<</SYS>>\\n\\n' + message['content'] %}"
-            "{% else %}"
-            "{% set content = message['content'] %}"
-            "{% endif %}"
-            "{% if message['role'] == 'user' %}"  # After all of that, handle messages/roles in a fairly normal way
-            "{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}"
-            "{% elif message['role'] == 'system' %}"
-            "{{ '<<SYS>>\\n' + content.strip() + '\\n<</SYS>>\\n\\n' }}"
-            "{% elif message['role'] == 'assistant' %}"
-            "{{ ' '  + content.strip() + ' ' + eos_token }}"
-            "{% endif %}"
-            "{% endfor %}"
-        )
-        template = template.replace("USE_DEFAULT_PROMPT", "true" if self.use_default_system_prompt else "false")
-        default_message = DEFAULT_SYSTEM_PROMPT.replace("\n", "\\n").replace("'", "\\'")
-        template = template.replace("DEFAULT_SYSTEM_MESSAGE", default_message)
-
-        return template
-
     def build_inputs_with_special_tokens(
         self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None
     ) -> List[int]: