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Releases: huggingface/optimum-intel

v1.21.0: SD3, Flux, MiniCPM, NanoLlava, VLM Quantization, XPU, PagedAttention

06 Dec 12:53
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What's Changed

OpenVINO

Diffusers

VLMs Modeling

NNCF

IPEX

  • Unified XPU/CPU modeling with custom PagedAttention cache for LLMs by @sywangyi in #1009

INC

New Contributors

Full Changelog: v1.20.0...v1.21.0

v1.20.1: Patch release

30 Oct 14:08
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  • Fix lora unscaling in diffusion pipelines by @eaidova in #937
  • Fix compatibility with diffusers < 0.25.0 by @eaidova in #952
  • Allow to use SDPA in clip models by @eaidova in #941
  • Updated OVPipelinePart to have separate ov_config by @e-ddykim in #957
  • Symbol use in optimum: fix misprint by @jane-intel in #948
  • Fix temporary directory saving by @eaidova in #959
  • Disable warning about tokenizers version for ov tokenizers >= 2024.5 by @eaidova in #962
  • Restore original model_index.json after save_pretrained call by @eaidova in #961
  • Add v4.46 transformers support by @echarlaix in #960

v1.20.0: multi-modal and OpenCLIP models support, transformers v4.45

10 Oct 17:01
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OpenVINO

Multi-modal models support

Adding OVModelForVisionCausalLM by @eaidova in #883

OpenCLIP models support

Adding OpenCLIP models support by @sbalandi in #857

from optimum.intel import OVModelCLIPVisual, OVModelCLIPText

visual_model = OVModelCLIPVisual.from_pretrained(model_name_or_path)
text_model  = OVModelCLIPText.from_pretrained(model_name_or_path)
image = processor(image).unsqueeze(0)
text = tokenizer(["a diagram", "a dog", "a cat"])
image_features = visual_model(image).image_features
text_features = text_model(text).text_features

Diffusion pipeline

Adding OVDiffusionPipeline to simplify diffusers model loading by @IlyasMoutawwakil in #889

  model_id = "stabilityai/stable-diffusion-xl-base-1.0"
- pipeline = OVStableDiffusionXLPipeline.from_pretrained(model_id)
+ pipeline = OVDiffusionPipeline.from_pretrained(model_id)
  image = pipeline("sailing ship in storm by Leonardo da Vinci").images[0]

NNCF GPTQ support

GPTQ support by @nikita-savelyevv in #912

Transformers v4.45

Transformers v4.45 support by @echarlaix in #902

Subfolder

Remove the restriction for the model's config to be in the model's subfolder by @tomaarsen in #933

New Contributors

v1.19.0: SentenceTransformers OpenVINO support

10 Sep 21:57
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from optimum.intel import OVSentenceTransformer

model_id = "sentence-transformers/all-mpnet-base-v2"
model = OVSentenceTransformer.from_pretrained(model_id, export=True)
sentences = ["This is an example sentence", "Each sentence is converted"]
embeddings = model.encode(sentences)
  • Infer if the model needs to be exported or not by @echarlaix in #825
  from optimum.intel import OVModelForCausalLM

- model = OVModelForCausalLM.from_pretrained("gpt2", export=True)
+ model = OVModelForCausalLM.from_pretrained("gpt2")

Compatible with transformers>=4.36,<=4.44

Full Changelog: v1.18.0...v1.19.0

v1.18.3: Patch release

19 Aug 09:16
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v1.18.2: Patch release

06 Aug 16:13
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Full Changelog: v1.18.1...v1.18.2

v1.18.1: Patch release

09 Jul 16:13
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Full Changelog: v1.18.0...v1.18.1

v1.18.0: Arctic, Jais, OpenVINO pipelines

26 Jun 23:21
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OpenVINO

from optimum.intel.pipelines import pipeline

# Load openvino model
ov_pipe = pipeline("text-generation", "helenai/gpt2-ov", accelerator="openvino")
# Load pytorch model and convert it to openvino before inference
pipe = pipeline("text-generation", "gpt2", accelerator="openvino")

IPEX

v1.17.2: Patch release

07 Jun 19:14
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v1.17.1: Patch release

06 Jun 15:40
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