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docs - vtx ft api
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@ -13,6 +13,7 @@ This is an Enterprise only endpoint [Get Started with Enterprise here](https://c
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## Supported Providers
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- Azure OpenAI
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- OpenAI
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- Vertex AI
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Add `finetune_settings` and `files_settings` to your litellm config.yaml to use the fine-tuning endpoints.
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## Example config.yaml for `finetune_settings` and `files_settings`
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@ -32,6 +33,10 @@ finetune_settings:
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api_version: "2023-03-15-preview"
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- custom_llm_provider: openai
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api_key: os.environ/OPENAI_API_KEY
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- custom_llm_provider: "vertex_ai"
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vertex_project: "adroit-crow-413218"
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vertex_location: "us-central1"
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vertex_credentials: "/Users/ishaanjaffer/Downloads/adroit-crow-413218-a956eef1a2a8.json"
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# for /files endpoints
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files_settings:
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@ -73,6 +78,9 @@ curl http://localhost:4000/v1/files \
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## Create fine-tuning job
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<Tabs>
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<TabItem value="azure" label="Azure OpenAI">
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<Tabs>
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<TabItem value="openai" label="OpenAI Python SDK">
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@ -100,6 +108,40 @@ curl http://localhost:4000/v1/fine_tuning/jobs \
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</TabItem>
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</Tabs>
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</TabItem>
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<TabItem value="Vertex" label="VertexAI">
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<Tabs>
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<TabItem value="openai" label="OpenAI Python SDK">
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```python
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ft_job = await client.fine_tuning.jobs.create(
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model="gemini-1.0-pro-002", # Vertex model you want to fine-tune
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training_file="gs://cloud-samples-data/ai-platform/generative_ai/sft_train_data.jsonl", # file_id from create file response
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extra_body={"custom_llm_provider": "vertex_ai"}, # tell litellm proxy which provider to use
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)
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```
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</TabItem>
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<TabItem value="curl" label="curl">
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```shell
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curl http://localhost:4000/v1/fine_tuning/jobs \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer sk-1234" \
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-d '{
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"custom_llm_provider": "vertex_ai",
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"model": "gemini-1.0-pro-002",
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"training_file": "gs://cloud-samples-data/ai-platform/generative_ai/sft_train_data.jsonl"
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}'
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```
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</TabItem>
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</Tabs>
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</TabItem>
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</Tabs>
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## Cancel fine-tuning job
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<Tabs>
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