support added for HF SmolLM3-3B

[AshutoshSinghIntel]

What does this PR do?

OpenVINO export:

optimum-cli export openvino -m HuggingFaceTB/SmolLM3-3B ./SmolLM3-3B --task text-generation-with-past

Inference Script:

import argparse
from transformers import AutoTokenizer
from optimum.intel.openvino import OVModelForCausalLM

model_id = "HuggingFaceTB/SmolLM3-3B"

def main():
    parser = argparse.ArgumentParser(description="SmolLM3-3B inference with OpenVINO")
    parser.add_argument("--model", type=str, default=model_id, help="Path to exported OV model or HF model ID")
    parser.add_argument("--max-new-tokens", type=int, default=100)
    parser.add_argument("--device", type=str, default="CPU")
    args = parser.parse_args()

    model = OVModelForCausalLM.from_pretrained(args.model, device=args.device)
    tokenizer = AutoTokenizer.from_pretrained(args.model)

    messages = [
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is the capital of France?"},
    ]

    inputs = tokenizer.apply_chat_template(messages, tokenize=True, return_dict=True, return_tensors="pt", add_generation_prompt=True)
    output = model.generate(**inputs, max_new_tokens=args.max_new_tokens)
    print(tokenizer.decode(output[0, inputs["input_ids"].shape[1]:], skip_special_tokens=True))

if __name__ == "__main__":
    main()

Fixes # CVS-183437

Before submitting

• [N/A] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
• Did you make sure to update the documentation with your changes?
• Did you write any new necessary tests?

[HuggingFaceDocBuilderDev]

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

[rkazants]

please provide proper PR description with code snippets for export and inference. See reference #1688

The other part looks good to me

[Copilot]

Pull request overview

Adds OpenVINO export support for the HuggingFace Transformers smollm3 architecture (SmolLM3-3B), wiring it into the OpenVINO TasksManager configs, test matrices, and the supported-models documentation.

Changes:

• Register a new SmolLM3OpenVINOConfig (Llama-based) for multiple tasks with a minimum transformers version of 4.53.0.
• Extend OpenVINO exporter and GenAI/decoder/CLI test coverage to include smollm3, and add a tiny internal test model id.
• Update OpenVINO supported-architectures documentation to list SmolLM3, and remove smollm3 from the “ONNX supported but untested” warning set.

Reviewed changes

Copilot reviewed 8 out of 8 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
optimum/exporters/openvino/model_configs.py	Registers smollm3 in the OpenVINO TasksManager with an OpenVINO config class and version gate.
optimum/exporters/openvino/utils.py	Removes smollm3 from ONNX_SUPPORTED_ARCHITECTURES so it’s no longer treated as “untested / export at your own risk”.
tests/openvino/utils_tests.py	Adds an internal tiny test model mapping for smollm3.
tests/openvino/test_genai.py	Includes smollm3 in the GenAI LLM pipeline supported-architecture matrix for transformers>=4.53.0.
tests/openvino/test_exporters_cli.py	Adds CLI export test coverage and expected tokenizer artifact counts for smollm3.
tests/openvino/test_export.py	Adds smollm3 to the export integration test architecture mapping.
tests/openvino/test_decoder.py	Adds smollm3 to the decoder integration supported-architecture matrix for transformers>=4.53.0.
docs/source/openvino/models.mdx	Documents SmolLM3 as a supported architecture.

---

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[regisss]

LGTM.
I agree with @rkazants' comment, let's stay consistent with previous PRs please.

[AshutoshSinghIntel]

Thanks @rkazants and @regisss , I have updated the PR description.

[AshutoshSinghIntel]

@IlyasMoutawwakil Could you please provide me access to https://huggingface.co/optimum-intel-internal-testing for uploading the tiny-random-smollm3 ? I ran it locally and tests are passing.

[rkazants]

@popovaan, please take a look:

1. check real model work
2. ask for wwb metrics

[AshutoshSinghIntel]

The WWB similarity score is 1.0 (using CPU, fp16, and the default number of samples, which was 27).

Similarity evaluation:  96%|#########6| 
26/27 [00:05<00:00,  5.61it/s]
Similarity evaluation: 100%|##########| 
27/27 [00:05<00:00,  5.67it/s]
Similarity evaluation: 100%|##########| 
27/27 [00:05<00:00,  4.74it/s]
INFO:whowhatbench.wwb:Metrics for model: SmolLM3-3B
INFO:whowhatbench.wwb:   similarity
0         1.0

[AshutoshSinghIntel]

Below is the script for creating tiny-model (I do not have the access to publish yet):

from transformers import (
    AutoTokenizer,
    SmolLM3Config,
    SmolLM3ForCausalLM,
)

def create_tiny_random_smollm3():

    config = SmolLM3Config(
        vocab_size=128256,
        hidden_size=32,
        intermediate_size=64,
        num_hidden_layers=2,
        num_attention_heads=4,
        num_key_value_heads=2,
        max_position_embeddings=256,
        hidden_act="silu",
        rms_norm_eps=1e-6,
        tie_word_embeddings=True,
        use_cache=True,
        attention_bias=False,
        mlp_bias=False,
        use_sliding_window=False,
        pad_token_id=128004,
        bos_token_id=128000,
        eos_token_id=128012,
    )

    model = SmolLM3ForCausalLM(config)
    print(f"Model parameters: {sum(p.numel() for p in model.parameters()):,}")

    # Use SmolLM3-3B tokenizer
    tokenizer = AutoTokenizer.from_pretrained("HuggingFaceTB/SmolLM3-3B")

    output_dir = "./tiny-random-smollm3"
    model.save_pretrained(output_dir)
    tokenizer.save_pretrained(output_dir)
    print(f"Saved to {output_dir}")

if __name__ == "__main__":
    create_tiny_random_smollm3()

[popovaan]

Please add quantization tests.

[popovaan]

There was a warning during conversion of the model "The OpenVINO export of smollm3 models is not officially supported by optimum-intel, export at your own risks.", was it fixed?

[AshutoshSinghIntel]

There was a warning during conversion of the model "The OpenVINO export of smollm3 models is not officially supported by optimum-intel, export at your own risks.", was it fixed?

With the dedicated config added by this PR, the warning does not appear.

[AshutoshSinghIntel]

Please add quantization tests.

added, kindly check.

[popovaan]

@rkazants @echarlaix @regisss please review this PR.

[regisss]

LGTM

[AshutoshSinghIntel]

Hi @regisss and @rkazants , kindly help to re-review. I updated code to take care of different int8 count expectation based on different task in a single model.

e.g. in SmolLM3-3B,
text-generation-with-past: 30
feature-extraction: 30
text-classification: 32