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feat: add example using fallback

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NanoCode012
2024-10-14 12:22:22 +07:00
parent 24aa6b15a0
commit e5cd55cff9
1 changed files with 12 additions and 3 deletions
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docs/dataset-formats/conversation.qmd
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@@ -127,7 +127,6 @@ We recommend checking the below examples for other usecases.
datasets: datasets:
- path: ... - path: ...
type: chat_template type: chat_template
# chat_template: tokenizer_default # This is the default value
``` ```
2. Using the `gemma` chat template to override the tokenizer_config.json's chat template on OpenAI messages format, training on all assistant messages. 2. Using the `gemma` chat template to override the tokenizer_config.json's chat template on OpenAI messages format, training on all assistant messages.
@@ -140,7 +139,17 @@ datasets:
roles_to_train: ["assistant"] roles_to_train: ["assistant"]
``` ```
3. Using a custom jinja template on OpenAI messages format, training on all assistant messages. 3. Using the tokenizer_config.json's chat template or `chatml` as fallback if the former's chat template does not exist, on OpenAI messages format, training on all assistant messages.
```yaml
chat_template: tokenizer_default_fallback_chatml # this overwrites the tokenizer's chat_template
datasets:
- path: ...
type: chat_template
roles_to_train: ["assistant"]
```
4. Using a custom jinja template on OpenAI messages format, training on all assistant messages.
```yaml ```yaml
# chat_template: jinja # `jinja` will be implied if the `chat_template_jinja` is set and this field is empty # chat_template: jinja # `jinja` will be implied if the `chat_template_jinja` is set and this field is empty
@@ -152,7 +161,7 @@ datasets:
roles_to_train: ["assistant"] roles_to_train: ["assistant"]
``` ```
4. (Advanced) Using fine-grained control over tokens and turns to train in a conversation 5. (Advanced) Using fine-grained control over tokens and turns to train in a conversation
For a data sample that looks like: For a data sample that looks like: