accelerate

https://github.com/huggingface/accelerate

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Official organization for the Hugging Face Accelerate library

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marcsun13 new activity 3 days ago

hf-accelerate/model-memory-usage:Error accessing Llama4 models: 'does not have any library metadata on the Hub'

marcsun13 updated a Space 3 days ago

hf-accelerate/model-memory-usage

marcsun13 new activity 11 days ago

hf-accelerate/model-memory-usage:GPTQ group size effects vRAM usage

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hf-accelerate's activity

marcsun13

in hf-accelerate/model-memory-usage 3 days ago

Error accessing Llama4 models: 'does not have any library metadata on the Hub'

#39 opened 12 days ago by

asharma2024

marcsun13

updated a Space 3 days ago

937

Model Memory Utility

🚀

Calculate memory usage for training models

marcsun13

in hf-accelerate/model-memory-usage 11 days ago

GPTQ group size effects vRAM usage

#18 opened over 1 year ago by

sgjohnson

Determining Minimum GPU Memory and Input Text Length Calculation in Model Training

#19 opened over 1 year ago by

kobe8-24

microsoft/Florence-2-base raises error without any detail

#36 opened 8 months ago by

fcakyon

For Llama-2 model, I tried to get the memory usage, it says I do not have the access

#35 opened 8 months ago by

AiEvanTao

Improve name of the model detection to allow several URL usages

#28 opened about 1 year ago by

Pablohn26

meta-llama/Meta-Llama-3.1-8B-Instruct ....why not found this

#34 opened 8 months ago by

world-of-ai

Llama3 is not found using link and API token

#31 opened 12 months ago by

barnaszocs

Question about Gradient calculation

#30 opened 12 months ago by

Infinity4B

How to Calculate GPU usage for re-training Microsoft/speechT5_tts ?

#27 opened about 1 year ago by

huggingfacerohit

Unable to Access Gated Model Repository databricks/dbrx-instruct

#26 opened about 1 year ago by

lambda1989

Data Wrong, THUDM/chatglm3-6b

#20 opened over 1 year ago by

YEKANGMING

Analyzing tool for inference

#13 opened over 1 year ago by

cllatMTK

Dropdown menu of models

#2 opened over 1 year ago by

Ouz-G

Plz fix it!!!

#33 opened 10 months ago by

DonDonDon

This space is no longer working

#38 opened 3 months ago by

LuisVasquezBSC

Wauplin

posted an update about 1 month ago

Post

2132

‼️ huggingface_hub's v0.30.0 is out with our biggest update of the past two years!

Full release notes: https://github.com/huggingface/huggingface_hub/releases/tag/v0.30.0.

🚀 Ready. Xet. Go!

Xet is a groundbreaking new protocol for storing large objects in Git repositories, designed to replace Git LFS. Unlike LFS, which deduplicates files, Xet operates at the chunk level—making it a game-changer for AI builders collaborating on massive models and datasets. Our Python integration is powered by [xet-core](https://github.com/huggingface/xet-core), a Rust-based package that handles all the low-level details.

You can start using Xet today by installing the optional dependency:

pip install -U huggingface_hub[hf_xet]

With that, you can seamlessly download files from Xet-enabled repositories! And don’t worry—everything remains fully backward-compatible if you’re not ready to upgrade yet.

Blog post: https://huggingface.co/blog/xet-on-the-hub
Docs: https://huggingface.co/docs/hub/en/storage-backends#xet

⚡ Inference Providers

- We’re thrilled to introduce Cerebras and Cohere as official inference providers! This expansion strengthens the Hub as the go-to entry point for running inference on open-weight models.

- Novita is now our 3rd provider to support text-to-video task after Fal.ai and Replicate.

- Centralized billing: manage your budget and set team-wide spending limits for Inference Providers! Available to all Enterprise Hub organizations.

from huggingface_hub import InferenceClient
client = InferenceClient(provider="fal-ai", bill_to="my-cool-company")
image = client.text_to_image(
    "A majestic lion in a fantasy forest",
    model="black-forest-labs/FLUX.1-schnell",
)
image.save("lion.png")

- No more timeouts when generating videos, thanks to async calls. Available right now for Fal.ai, expecting more providers to leverage the same structure very soon!

6 replies

lysandre

posted an update 3 months ago

Post

6572

SmolVLM-2 and SigLIP-2 are now part of transformers in dedicated releases!

They're added on top of the v4.49.0 release, and can be installed from the following tags: v4.49.0-SmolVLM-2 and v4.49.0-SigLIP-2.

This marks a new beginning for the release process of transformers. For the past five years, we've been doing monthly releases featuring many models (v4.49.0, the latest release, features 9 new architectures).

Starting with SmolVLM-2 & SigLIP2, we'll now additionally release tags supporting new models on a stable branch. These models are therefore directly available for use by installing from the tag itself. These tags will continue to be updated with fixes applied to these models.

Going forward, continue expecting software releases following semantic versioning: v4.50.0 will have ~10 new architectures compared to v4.49.0, as well as a myriad of new features, improvements and bug fixes. Accompanying these software releases, we'll release tags offering brand new models as fast as possible, to make them accessible to all immediately.