📄 Llava¶

formats.models.llava

type: HFSystemFormat
model_name: llava-hf/llava-1.5-7b-hf
[source]

Explanation about HFSystemFormat¶

Formats the complete input for the model using the HuggingFace chat template of a given model.

HFSystemFormat expects the input instance to contain: 1. A field named “system_prompt” whose value is a string (potentially empty) that delivers a task-independent opening text. 2. A field named “source” whose value is a string verbalizing the original values in the instance (as read from the source dataset), in the context of the underlying task. 3. A field named “instruction” that contains a (non-None) string. 4. A field named with the value in arg ‘demos_field’, containing a list of dicts, each dict with fields “source” and “target”, representing a single demo. 5. A field named “target_prefix” that contains a string to prefix the target in each demo, and to end the whole generated prompt.

SystemFormat formats the above fields into a single string to be inputted to the model. This string overwrites field “source” of the instance.

Example:
HFSystemFormat(model_name=”HuggingFaceH4/zephyr-7b-beta”)

Uses the template defined the in tokenizer_config.json of the model:

“chat_template”: “{% for message in messages %}n{% if message[‘role’] == ‘user’ %}n{{ ‘<|user|>n’ + message[‘content’] + eos_token }}n{% elif message[‘role’] == ‘system’ %}n{{ ‘<|system|>n’ + message[‘content’] + eos_token }}n{% elif message[‘role’] == ‘assistant’ %}n{{ ‘<|assistant|>n’ + message[‘content’] + eos_token }}n{% endif %}n{% if loop.last and add_generation_prompt %}n{{ ‘<|assistant|>’ }}n{% endif %}n{% endfor %}”,

See more details in https://huggingface.co/docs/transformers/main/en/chat_templating