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aiondemand / AIOD-rest-api

Services for the core of AIoD: Authentication and the metadata catalogue with REST API.
https://api.aiod.eu
MIT License
10 stars 7 forks source link

Bump huggingface-hub from 0.20.3 to 0.22.2 #294

Closed dependabot[bot] closed 5 months ago

dependabot[bot] commented 6 months ago

Bumps huggingface-hub from 0.20.3 to 0.22.2.

Release notes

Sourced from huggingface-hub's releases.

[v0.22.2] Hot-fix: correctly handle proxies

Full Changelog: https://github.com/huggingface/huggingface_hub/compare/v0.22.1...v0.22.2

See huggingface/huggingface_hub#2155 and huggingface/huggingface_hub#2167 for more details.

[v0.22.1] Hot-fix: correctly handle dataclasses in ModelHubMixin

Fixed a bug breaking the SetFit integration.

What's Changed

Full Changelog: https://github.com/huggingface/huggingface_hub/compare/v0.22.0...v0.22.1

v0.22.0: Chat completion, inference types and hub mixins!

Discuss about the release in our Community Tab. Feedback is welcome!! 🤗

✨ InferenceClient

Support for inference tools continues to improve in huggingface_hub. At the menu in this release? A new chat_completion API and fully typed inputs/outputs!

Chat-completion API!

A long-awaited API has just landed in huggingface_hub! InferenceClient.chat_completion follows most of OpenAI's API, making it much easier to integrate with existing tools.

Technically speaking it uses the same backend as the text-generation task but requires a preprocessing step to format the list of messages into a single text prompt. The chat template is rendered server-side when models are powered by TGI, which is the case for most LLMs: Llama, Zephyr, Mistral, Gemma, etc. Otherwise, the templating happens client-side which requires minijinja package to be installed. We are actively working on bridging this gap, aiming at rendering all templates server-side in the future.

>>> from huggingface_hub import InferenceClient
>>> messages = [{"role": "user", "content": "What is the capital of France?"}]
>>> client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")

Batch completion


>>> client.chat_completion(messages, max_tokens=100)
ChatCompletionOutput(
choices=[
ChatCompletionOutputChoice(
finish_reason='eos_token',
index=0,
message=ChatCompletionOutputChoiceMessage(
content='The capital of France is Paris. The official name of the city is "Ville de Paris" (City of Paris) and the name of the country's governing body, which is located in Paris, is "La République française" (The French Republic). \nI hope that helps! Let me know if you need any further information.'
)
)
],
created=1710498360
)


Stream new tokens one by one


>>> for token in client.chat_completion(messages, max_tokens=10, stream=True):
</tr></table>

... (truncated)

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dependabot[bot] commented 5 months ago

Superseded by #305.