--- language: - en license: apache-2.0 library_name: gliclass pipeline_tag: zero-shot-classification base_model: knowledgator/gliclass-v4-edge model_name: Apex-flash tags: - apex - gliclass - gliclass-v4 - zero-shot-classification - text-classification - multi-label-classification - instruction-following - reranking --- # Apex-flash **Evidence in, decisions out.** Explore [SCX Apex](https://labs.scx.ai/apex), a family of GLiClass 4 based Large Decision Models. **A compact 0.4B Large Decision Model for high-volume text decisions.** Apex-flash brings instruction-guided decisions to CPUs and GPUs. Use it to route tickets, triage requests, apply policies, and choose the next action in your application. Part of the [SCX Apex family](https://huggingface.co/collections/scx-admin/apex-family-6ad58a4ea2e0c9875ddb4061), **based on GLiClass 4**. Give the model evidence, an instruction, and the answers you would accept. It scores the candidate answers in one forward pass without generating text. | Property | Value | | --- | --- | | Parameters | Approximately 0.4B | | Inputs | Text | | Backbone | [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) | | Framework | [GLiClass](https://github.com/Knowledgator/GLiClass) | | License | Apache 2.0 | ## Use an LLM to write. Use Apex to decide. - **Change the policy, not the model.** Supply instructions, policies, or rubrics at inference time, and change candidate answers as your workflow evolves. - **Act on confidence.** Use calibrated label scores to automate confident decisions and escalate uncertain cases to a person or an LLM. Validate thresholds on your own data. - **Make decisions directly.** Get structured label scores for routing, triage, moderation, ranking, extraction decisions, judging, and selecting the next step. ## Choose an Apex model | Model | Size | Inputs | Best suited to | | --- | --- | --- | --- | | [Apex-flash](https://huggingface.co/scx-admin/Apex-flash) | 0.4B | Text | High-volume decisions on CPU or GPU | | [Apex-large](https://huggingface.co/scx-admin/Apex-large) | 9B | Text and images | Knowledge-heavy and visual decisions | Explore the [Apex family collection](https://huggingface.co/collections/scx-admin/apex-family-6ad58a4ea2e0c9875ddb4061). Both releases provide open weights under Apache 2.0. ## Quick start Use Python 3.10+ and an up-to-date GLiClass installation: ```bash pip install -U gliclass ``` The example runs on a CUDA GPU when available and otherwise uses the CPU. ```python import torch from gliclass import GLiClassModel, ZeroShotClassificationPipeline model_id = "scx-admin/Apex-flash" device = "cuda:0" if torch.cuda.is_available() else "cpu" model = GLiClassModel.from_pretrained(model_id) pipeline = ZeroShotClassificationPipeline( model, model_id, classification_type="multi-label", max_length=2048, device=device, ) results = pipeline( "My parcel has not arrived. Please check the delivery status.", ["delivery issue", "refund request", "technical support"], threshold=0.5, )[0] for result in results: print(result["label"], result["score"]) ``` Pass `prompt="your instruction or policy"` to guide the decision. Use `classification_type="single-label"` for mutually exclusive choices. Multi-label results may contain more than one label or no labels above the threshold. ## Limitations Predictions depend on label wording, instructions, domain, input length, and thresholds. English is the primary language. Calibration can drift on new domains; evaluate scores and thresholds on representative data. See the [upstream model card](https://huggingface.co/knowledgator/gliclass-v4-edge) for training details, evaluations, and further limitations. ## Attribution and license This release republishes the upstream checkpoint under the Apex name. The weights, configuration, tokenizer, and other inference assets are unchanged; no additional fine-tuning is claimed. Based on **GLiClass 4**, developed by **Knowledgator**. Original checkpoint: [knowledgator/gliclass-v4-edge](https://huggingface.co/knowledgator/gliclass-v4-edge/tree/90be5550327b138635db1f63531f9dfa15e624da), revision `90be5550327b138635db1f63531f9dfa15e624da`. Distributed under the upstream **Apache License 2.0**; see [LICENSE](LICENSE). The original model card is preserved in [UPSTREAM_README.md](UPSTREAM_README.md) and at the upstream link. Related work: [GLiClass](https://arxiv.org/abs/2508.07662) and [SCX Router](https://arxiv.org/abs/2609.02292).