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hyperonym / basaran

Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
MIT License
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build(deps): update huggingface-hub requirement from ~=0.14.1 to ~=0.15.1 #201

Closed dependabot[bot] closed 1 year ago

dependabot[bot] commented 1 year ago

Updates the requirements on huggingface-hub to permit the latest version.

Release notes

Sourced from huggingface-hub's releases.

v0.15.1: InferenceClient and background uploads!

InferenceClient

We introduce InferenceClient, a new client to run inference on the Hub. The objective is to:

  • support both InferenceAPI and Inference Endpoints services in a single client.
  • offer a nice interface with:
    • 1 method per task (e.g. summary = client.summarization("this is a long text"))
    • 1 default model per task (i.e. easy to prototype)
    • explicit and documented parameters
    • convenient binary inputs (from url, path, file-like object,...)
  • be flexible and support custom requests if needed

Check out the Inference guide to get a complete overview.

>>> from huggingface_hub import InferenceClient
>>> client = InferenceClient()

>>> image = client.text_to_image("An astronaut riding a horse on the moon.")
>>> image.save("astronaut.png")


>>> client.image_classification("https://upload.wikimedia.org/wikipedia/commons/thumb/4/43/Cute_dog.jpg/320px-Cute_dog.jpg")
[{'score': 0.9779096841812134, 'label': 'Blenheim spaniel'}, ...]

The short-term goal is to add support for more tasks (here is the current list), especially text-generation and handle asyncio calls. The mid-term goal is to deprecate and replace InferenceAPI.

Non-blocking uploads

It is now possible to run HfApi calls in the background! The goal is to make it easier to upload files periodically without blocking the main thread during a training. The was previously possible when using Repository but is now available for HTTP-based methods like upload_file, upload_folder and create_commit. If run_as_future=True is passed:

  • the job is queued in a background thread. Only 1 worker is spawned to ensure no race condition. The goal is NOT to speed up a process by parallelizing concurrent calls to the Hub.
  • a Future object is returned to check the job status
  • main thread is not interrupted, even if an exception occurs during the upload

In addition to this parameter, a run_as_future(...) method is available to queue any other calls to the Hub. More details in this guide.

>>> from huggingface_hub import HfApi

>>> api = HfApi()
>>> api.upload_file(...)  # takes Xs


URL to upload file


>>> future = api.upload_file(..., run_as_future=True) # instant
>>> future.result() # wait until complete


URL to upload file

... (truncated)

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