docs add example doing ft

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Ishaan Jaff 2024-07-31 17:19:00 -07:00
parent 82948fccc7
commit df684cbf6f

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@ -1,3 +1,6 @@
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
# [Beta] Fine-tuning API # [Beta] Fine-tuning API
@ -11,7 +14,7 @@ This is an Enterprise only endpoint [Get Started with Enterprise here](https://c
- Azure OpenAI - Azure OpenAI
- OpenAI - OpenAI
Add `finetune_settings` and `files_settings` to your litellm config.yaml to use the fine-tuning endpoints.
## Usage ## Usage
```yaml ```yaml
model_list: model_list:
@ -25,7 +28,7 @@ model_list:
finetune_settings: finetune_settings:
- custom_llm_provider: azure - custom_llm_provider: azure
api_base: https://exampleopenaiendpoint-production.up.railway.app api_base: https://exampleopenaiendpoint-production.up.railway.app
api_key: fake-key api_key: os.environ/AZURE_API_KEY
api_version: "2023-03-15-preview" api_version: "2023-03-15-preview"
- custom_llm_provider: openai - custom_llm_provider: openai
api_key: os.environ/OPENAI_API_KEY api_key: os.environ/OPENAI_API_KEY
@ -42,9 +45,33 @@ files_settings:
## Create File for Fine Tuning ## Create File for Fine Tuning
<Tabs>
<TabItem value="openai" label="OpenAI Python v1.0.0+">
```python
client = AsyncOpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000") # base_url is your litellm proxy url
file_name = "openai_batch_completions.jsonl"
response = await client.files.create(
extra_body={"custom_llm_provider": "azure"}, # tell litellm proxy which provider to use
file=open(file_name, "rb"),
purpose="fine-tune",
)
```
</TabItem>
</Tabs>
## Create fine-tuning job ## Create fine-tuning job
<Tabs>
</Tabs>
## Cancel fine-tuning job ## Cancel fine-tuning job
<Tabs>
</Tabs>
## List fine-tuning jobs ## List fine-tuning jobs
<Tabs>
</Tabs>