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docs/source/basic_tutorials/consuming_tgi.md
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@ -16,8 +16,7 @@ curl 127.0.0.1:8080/generate \
## Inference Client ## Inference Client
[`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 nice high-level class, [`~huggingface_hub.InferenceClient`], which makes it easy to make calls to a TGI endpoint. `InferenceClient` also takes care of parameter validation and provides a simple to-use interface. At the moment, `InferenceClient` only works for models hosted with the Inference API or Inference Endpoints. [`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 nice high-level class, [`~huggingface_hub.InferenceClient`], which makes it easy to make calls to a TGI endpoint. `InferenceClient` also takes care of parameter validation and provides a simple to-use interface.
You can simply install `huggingface-hub` package with pip. You can simply install `huggingface-hub` package with pip.
```bash ```bash
@ -29,7 +28,7 @@ Once you start the TGI server, instantiate `InferenceClient()` with the URL to t
```python ```python
from huggingface_hub import InferenceClient from huggingface_hub import InferenceClient
client = InferenceClient(model=URL_TO_ENDPOINT_SERVING_TGI) client = InferenceClient(model="http://127.0.0.1:8080")
client.text_generation(prompt="Write a code for snake game") client.text_generation(prompt="Write a code for snake game")
``` ```
@ -52,7 +51,7 @@ print(output)
You can see how to stream below. You can see how to stream below.
```python ```python
output = client.text_generation(prompt="Meaning of life is", model="http://localhost:3000/", stream=True, details=True) output = client.text_generation(prompt="Meaning of life is", stream=True, details=True)
print(next(iter(output))) print(next(iter(output)))
# TextGenerationStreamResponse(token=Token(id=267, text=' a', logprob=-2.0723474, special=False), generated_text=None, details=None) # TextGenerationStreamResponse(token=Token(id=267, text=' a', logprob=-2.0723474, special=False), generated_text=None, details=None)