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SOLID-Qwen3

AIOR-Research / SOLID-Qwen3

Run on huggingface.co
huggingface.co
Total runs: 941
24-hour runs: 4
7-day runs: 37
30-day runs: 892
Model's Last Updated: September 10 2026
text-generation

Introduction of SOLID-Qwen3

Model Details of SOLID-Qwen3

SOLID-opt

SOLID-opt is trained from Qwen3-4B-Instruct-2507, specialized for operations-research modeling. It is intended to turn natural-language optimization problems into structured reasoning, linear-programming formulations, and solver-oriented Python code.

Training combines GRPO, solver-objective majority voting, and teacher KL localized with solver-information signals. The training configuration uses Gurobi-style nine-step outputs.

Quick start 
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "JR-James-0125/SOLID-opt"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype="auto",
    device_map="auto",
)

messages = [
    {"role": "user", "content": "Formulate and solve this optimization problem: ..."}
]
inputs = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt=True,
    return_tensors="pt",
).to(model.device)

outputs = model.generate(inputs, max_new_tokens=2048)
print(tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True))
Intended use and limitations

This model is released for research on mathematical optimization and operations-research reasoning. Generated formulations, coefficients, constraints, solver code, and claimed solutions may be incorrect, infeasible, or unsafe to use without review. Validate outputs with an appropriate solver and independent checks before using them in consequential settings.

No standalone evaluation results are included in this initial model card.

Runs of AIOR-Research SOLID-Qwen3 on huggingface.co

941
Total runs
4
24-hour runs
16
3-day runs
37
7-day runs
892
30-day runs

More Information About SOLID-Qwen3 huggingface.co Model

SOLID-Qwen3 huggingface.co

SOLID-Qwen3 huggingface.co is an AI model on huggingface.co that provides SOLID-Qwen3's model effect (), which can be used instantly with this AIOR-Research SOLID-Qwen3 model. huggingface.co supports a free trial of the SOLID-Qwen3 model, and also provides paid use of the SOLID-Qwen3. Support call SOLID-Qwen3 model through api, including Node.js, Python, http.

SOLID-Qwen3 huggingface.co Url

https://huggingface.co/AIOR-Research/SOLID-Qwen3

AIOR-Research SOLID-Qwen3 online free

SOLID-Qwen3 huggingface.co is an online trial and call api platform, which integrates SOLID-Qwen3's modeling effects, including api services, and provides a free online trial of SOLID-Qwen3, you can try SOLID-Qwen3 online for free by clicking the link below.

AIOR-Research SOLID-Qwen3 online free url in huggingface.co:

https://huggingface.co/AIOR-Research/SOLID-Qwen3

SOLID-Qwen3 install

SOLID-Qwen3 is an open source model from GitHub that offers a free installation service, and any user can find SOLID-Qwen3 on GitHub to install. At the same time, huggingface.co provides the effect of SOLID-Qwen3 install, users can directly use SOLID-Qwen3 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

SOLID-Qwen3 install url in huggingface.co:

https://huggingface.co/AIOR-Research/SOLID-Qwen3

Url of SOLID-Qwen3

Provider of SOLID-Qwen3 huggingface.co

AIOR-Research
ORGANIZATIONS
huggingface.co

Other API from AIOR-Research