Bump huggingface-hub from 0.30.2 to 0.31.1 in /requirements
Type: Pull Request
State: Open
Association: Contributor
Comments: 0
(7 months ago)
(7 months ago)
dependencies python
Bumps huggingface-hub from 0.30.2 to 0.31.1.
Release notes
Sourced from huggingface-hub's releases.
[v0.31.0] LoRAs with Inference Providers,
automode for provider selection, embeddings models and more🧑‍🎨 Introducing LoRAs with fal.ai and Replicate providers
We're introducing blazingly fast LoRA inference powered by fal.ai and Replicate through Hugging Face Inference Providers! You can use any compatible LoRA available on the Hugging Face Hub and get generations at lightning fast speed ⚡
from huggingface_hub import InferenceClientclient = InferenceClient(provider="fal-ai") # or provider="replicate"
output is a PIL.Image object
image = client.text_to_image( "a boy and a girl looking out of a window with a cat perched on the window sill. There is a bicycle parked in front of them and a plant with flowers to the right side of the image. The wall behind them is visible in the background.", model="openfree/flux-chatgpt-ghibli-lora", )
- [Inference Providers] LoRAs with Replicate by
@​hanouticelinain #3054- [Inference Providers] Support for LoRAs with fal by
@​hanouticelinain #3005⚙️
automode for provider selectionYou can now automatically select a provider for a model using
automode — it will pick the first available provider based on your preferred order set in https://hf.co/settings/inference-providers.from huggingface_hub import InferenceClientwill select the first provider available for the model, sorted by your order.
client = InferenceClient(provider="auto")
completion = client.chat.completions.create( model="Qwen/Qwen3-235B-A22B", messages=[ { "role": "user", "content": "What is the capital of France?" } ], )
print(completion.choices[0].message)
⚠️ Note: This is now the default value for the
providerargument. Previously, the default washf-inference, so this change may be a breaking one if you're not specifying the provider name when initializingInferenceClientorAsyncInferenceClient.
- PoC:
provider="auto"by@​julien-cin #3011🧠Embeddings support with Sambanova (feature-extraction)
We added support for feature extraction (embeddings) inference with sambanova provider.
... (truncated)
Commits
13a3991Release: v0.31.1e2277d1fix conda (#3058)153f159Release: v0.31.08348905Release: v0.31.0.rc0ca7342dMigrate tologger.warningusage (#3056)df9f47bsupport loras with replicate (#3054)1e40c62[Inference Providers] fix inference with URL endpoints (#3041)caeaeebXet Upload with byte array (#3035)2bafd2aAdd the 'env' parameter to creating/updating Inference Endpoints (#3045)fff83afUpdate inference types (automated commit) (#3051)- Additional commits viewable in compare view
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Pull Request Statistics
1
2
+2
-2
Package Dependencies
huggingface-hub
pip
0.30.2 → 0.31.1
Minor
/requirements
Technical Details
| ID: | 86186 |
| UUID: | 2505833410 |
| Node ID: | PR_kwDOClTaK86VW_vC |
| Host: | GitHub |
| Repository: | qubvel-org/segmentation_models.pytorch |
| Merge State: | Unknown |