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Merge branch 'vb/update-consuming-tgi-docs' of https://github.com/Vaibhavs10/text-generation-inference into vb/update-consuming-tgi-docs
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@ -4,7 +4,7 @@ There are many ways to consume Text Generation Inference (TGI) server in your ap
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For more information on the API, consult the OpenAPI documentation of `text-generation-inference` available [here](https://huggingface.github.io/text-generation-inference).
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You can make the requests using any tool of your preference, such as curl, Python or TypeScript. For an end-to-end experience, we've open-sourced ChatUI, a chat interface for open-source models.
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You can make the requests using any tool of your preference, such as curl, Python, or TypeScript. For an end-to-end experience, we've open-sourced ChatUI, a chat interface for open-access models.
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## curl
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@ -68,7 +68,7 @@ for message in chat_completion:
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### Inference Client
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[`huggingface-hub`](https://huggingface.co/docs/huggingface_hub/main/en/index) is a Python library to interact with the Hugging Face Hub, including its endpoints. It provides a high-level class, [`huggingface_hub.InferenceClient`](https://huggingface.co/docs/huggingface_hub/package_reference/inference_client#huggingface_hub.InferenceClient), which makes it easy to make calls to TGI's Messages API. `InferenceClient` also takes care of parameter validation and provides a simple to-use interface.
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[`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/main/en/index) is a Python library to interact with the Hugging Face Hub, including its endpoints. It provides a high-level class, [`huggingface_hub.InferenceClient`](https://huggingface.co/docs/huggingface_hub/package_reference/inference_client#huggingface_hub.InferenceClient), which makes it easy to make calls to TGI's Messages API. `InferenceClient` also takes care of parameter validation and provides a simple-to-use interface.
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Install `huggingface_hub` package via pip.
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@ -87,7 +87,6 @@ You can now use `InferenceClient` the exact same way you would use `OpenAI` clie
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base_url="http://localhost:3000/v1/",
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)
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output = client.chat.completions.create(
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model="tgi",
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messages=[
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