Chat templates
SambaStudio allows you to add a chat template when uploading your own checkpoint. SambaStudio checkpoints also include a default chat template that can optionally be inherited when bringing in your own checkpoint or launching a training job.
Chat templates background
Chat templates specify how to convert conversations, or user inputs, into a special string format that the model expects. Chat templates provide the ability to submit meaningful inputs allowing the selected model to provide desired outputs.
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Chat templates can vary based on factors such as the model architecture and how a model is fine-tuned. Typically model architectures, or model families, include an associated chat template. For example, the Llama 2 family checkpoints generally use the following chat template.
<s>[INST] <<SYS>>
{system prompt}
<</SYS>>
{user message} [/INST]
Additionally, a checkpoint can be fine-tuned to use a different chat template. For example, Nous-Hermes-Llama2-13b, which is considered a fine-tuned derivative of Llama 2, uses the following chat template.
### Instruction:
<prompt>
### Input:
<additional context>
### Response:
<leave a newline blank for model to respond>
Lastly, chat templates can vary based on the application. For example, a checkpoint can use a different template for multi-turn or single-turn applications.
The same checkpoint can have multiple chat templates and different checkpoints can use the same chat template. |
View a chat template in a model card
The chat template for a model can be found in the corresponding model card.
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Edit chat templates in tokenizer_config.json
Checkpoints uploaded to SambaStudio typically contain a tokenizer_config.json
file. In this config file, a field called chat_template
specifies the prompt template for a checkpoint in Jinja format.
Some checkpoints may already contain a chat_template
field in the tokenizer_config.json
file specified by the checkpoint author. If this is the case, the chat_template
field will be consumed and read as a single string and interpreted as a jinja template. The template will be applied automatically if the process_prompt
field is set to True
. For example, the Hugging Face version of meta-llama/Meta-Llama-3.1-8B-Instruct contains a chat_template
field in its tokenizer_config.json
file, as shown below.
An empty string will be read as a valid prompt template ( |
"chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n {%- for arg_name, arg_val in tool_call.arguments | items %}\n {{- arg_name + '=\"' + arg_val + '\"' }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \")\" }}\n {%- else %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {%- endif %}\n {%- if builtin_tools is defined %}\n {#- This means we're in ipython mode #}\n {{- \"<|eom_id|>\" }}\n {%- else %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
How to write a prompt template using Jinja
To write a custom chat template that gets applied to a checkpoint by default, we use the Jinja template format. Jinja is a templating language where code can be written to generate text, based on varying scenarios and variables. Creating a Jinja template for a Large Language Model (LLM) involves setting up a structure that the LLM can dynamically populate with data.
{% if messages[0]['role'] == 'system' %}
{% set loop_messages = messages[1:] %}
{% set system_message = '<<SYS>>\n' + messages[0]['content'].strip() + '\n<</SYS>>\n\n' %}
{% else %}
{% set loop_messages = messages %}
{% set system_message = '' %}
{% endif %}
{% for message in loop_messages %}
{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}
{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}
{% endif %}
{% if loop.index0 == 0 %}
{% set content = system_message + message['content'] %}
{% else %}
{% set content = message['content'] %}
{% endif %}
{% if message['role'] == 'user' %}
{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}
{% elif message['role'] == 'assistant' %}
{{ ' ' + content.strip() + ' ' + eos_token }}
{% endif %}
{% endfor %}