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serge-chat / serge

A web interface for chatting with Alpaca through llama.cpp. Fully dockerized, with an easy to use API.
https://serge.chat
Apache License 2.0
5.68k stars 405 forks source link

Bump huggingface-hub from 0.25.2 to 0.26.0 in /api #1512

Closed dependabot[bot] closed 1 month ago

dependabot[bot] commented 1 month ago

Bumps huggingface-hub from 0.25.2 to 0.26.0.

Release notes

Sourced from huggingface-hub's releases.

v0.26.0: Multi-tokens support, conversational VLMs and quality of life improvements

🔐 Multiple access tokens support

Managing fine-grained access tokens locally just became much easier and more efficient! Fine-grained tokens let you create tokens with specific permissions, making them especially useful in production environments or when working with external organizations, where strict access control is essential.

To make managing these tokens easier, we've added a ✨ new set of CLI commands ✨ that allow you to handle them programmatically:

  • Store multiple tokens on your machine by simply logging in with the login() command with each token:
huggingface-cli login
  • Switch between tokens and choose the one that will be used for all interactions with the Hub:
huggingface-cli auth switch
  • List available access tokens on your machine:
huggingface-cli auth list
  • Delete a specific token from your machine with:
huggingface-cli logout [--token-name TOKEN_NAME]

✅ Nothing changes if you are using the HF_TOKEN environment variable as it takes precedence over the token set via the CLI. More details in the documentation. 🤗

⚡️ InferenceClient improvements

🖼️ Conversational VLMs support

Conversational vision-language models inference is now supported with InferenceClient's chat completion!

from huggingface_hub import InferenceClient

works with remote url or base64 encoded url


image_url ="https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"


client = InferenceClient("meta-llama/Llama-3.2-11B-Vision-Instruct")
output = client.chat.completions.create(
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {"url": image_url},
},
{
"type": "text",
"text": "Describe this image in one sentence.",
},
],
</tr></table>

... (truncated)

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dependabot[bot] commented 1 month ago

Superseded by #1514.