⬆️ Bump huggingface-hub from 0.24.6 to 0.28.1

[dependabot]

Bumps huggingface-hub from 0.24.6 to 0.28.1.

Release notes

Sourced from huggingface-hub's releases.

v0.28.1: FIX path in HF_ENDPOINT discarded

Release 0.28.0 introduced a bug making it impossible to set a HF_ENDPOINT env variable with a value with a subpath. This has been fixed in huggingface/huggingface_hub#2807.

Full Changelog: huggingface/huggingface_hub@v0.28.0...v0.28.1

[v0.28.0]: Third-party Inference Providers on the Hub & multiple quality of life improvements and bug fixes

⚡️Unified Inference Across Multiple Inference Providers

The InferenceClient now supports third-party providers, offering a unified interface to run inference across multiple services while leveraging models from the Hugging Face Hub. This update enables developers to:

• 🌐 Switch providers seamlessly - Transition between inference providers with a single interface.
• 🔗 Unified model IDs - Always reference Hugging Face Hub model IDs, even when using external providers.
• 🔑 Simplified billing and access management - You can use your Hugging Face Token for routing to third-party providers (billed through your HF account).

A list of supported third-party providers can be found here.

Example of text-to-image inference with Replicate:

>>> from huggingface_hub import InferenceClient
>>> replicate_client = InferenceClient(
...    provider="replicate",
...    api_key="my_replicate_api_key", # Using your personal Replicate key
)
>>> image = replicate_client.text_to_image(
...    "A cyberpunk cat hacking neural networks",
...    model="black-forest-labs/FLUX.1-schnell"
)
>>> image.save("cybercat.png")

Another example of chat completion with Together AI:

>>> from huggingface_hub import InferenceClient
>>> client = InferenceClient(
...     provider="together",  # Use Together AI provider
...     api_key="<together_api_key>",  # Pass your Together API key directly
... )
>>> client.chat_completion(
...     model="deepseek-ai/DeepSeek-R1",
...     messages=[{"role": "user", "content": "How many r's are there in strawberry?"}],
... )

When using external providers, you can choose between two access modes: either use the provider's native API key, as shown in the examples above, or route calls through Hugging Face infrastructure (billed to your HF account):

>>> from huggingface_hub import InferenceClient
>>> client = InferenceClient(
...    provider="fal-ai",
...    token="hf_****"  # Your Hugging Face token
</tr></table> 

... (truncated)

Commits

• dea8d04 Release: v0.28.1
• e0e891d fix(#2806): Replace urljoin for HF_ENDPOINT paths (#2807)
• 7cde837 Release: v0.28.0.rc4
• 865fa26 Release: v0.28.0
• 5ce79b2 Release: v0.28.0.rc3
• 67e88e1 [together] Remove and reclassify models (#2794)
• b0dee68 Fix super_squash_history revision not urlencoded (#2795)
• 7caf7da Release: v0.28.0.rc2
• 6b1f8d7 Release: v0.28.0.rc1
• b66934e Fix few things (inference providers) (#2793)
• Additional commits viewable in compare view

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