--- license: other license_name: noncommercial-research-only license_link: https://huggingface.co/webbrain-one/webbrain-compass-tiny-xs-v3/blob/main/README.md#license base_model: XHToken/Spark-X2.5-1.7B library_name: transformers pipeline_tag: text-generation tags: - webbrain - tool-calling - spark2_5 - lora --- # WebBrain Compass Tiny XS v3 WebBrain Compass Tiny XS v3 is a compact language model optimized for low-latency decision making, structured tool use, and in-browser agentic execution inside the WebBrain runtime. Fine-tuned from **Spark-X2.5-1.7B (~1.7B parameters)** (`XHToken/Spark-X2.5-1.7B` at `14d6e83c13c7add2b62a7c39b2131f4ed1cddcf8`), this is the BF16 reference model with merged weights, accompanied by the original LoRA adapter under `adapter/`. It unifies three core WebBrain behavioral modes: 1. **Ask & Clarify** — Answer directly or request missing information when execution is underspecified or unnecessary. 2. **Direct Compact Tool Execution** — Select exact browser tools and generate grounded arguments for low-latency accessibility-tree actions. 3. **Safe Escalation & Abstention** — Refuse, pause, or defer to higher execution tiers when actions lack adequate grounding or violate safety boundaries. > **Note:** Display/repository name is **WebBrain Compass Tiny XS v3**. This is a metadata-only rename preserving tested weight/code revision `main`. For native in-browser WebGPU execution, see the companion ONNX package: [`webbrain-one/webbrain-compass-tiny-xs-v3-onnx`](https://huggingface.co/webbrain-one/webbrain-compass-tiny-xs-v3-onnx). --- ## Role in WebBrain ```text User request │ ▼ WebBrain observation & policy layer │ ▼ WebBrain Compass Tiny XS v3 (BF16 Reference) ├─ Clarify or answer directly ├─ Emit grounded browser tool call └─ Abstain / safely escalate when execution is ungrounded ``` The outer WebBrain runtime enforces tool-schema validation, evidence and parameter grounding, destination URL verification, browser-state freshness, and sandboxed security policies. Model output is never proof that an external action succeeded. --- ## Intended Capabilities - **Browser Action Selection:** Grounded accessibility-tree interactions and structured function calling. - **Reference Decision Making:** Fast, high-fidelity local inference for compact browser actions. - **Unified Ask and Compact Modes:** Asking for missing information before acting, answering direct questions, or choosing tools. - **Safe Refusal & Escalation:** Refusing unsupported actions or escalating when Compact execution lacks evidence, avoiding invented URLs or fabricated success states. --- ## Quickstart & Loading You can load and run WebBrain Compass Tiny XS v3 directly with Hugging Face `transformers`: ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM repo = "webbrain-one/webbrain-compass-tiny-xs-v3" revision = "main" # Tested weight/code revision tokenizer = AutoTokenizer.from_pretrained(repo, revision=revision) model = AutoModelForCausalLM.from_pretrained( repo, revision=revision, trust_remote_code=True, dtype=torch.bfloat16, device_map="auto" ) # Example structured tool use messages = [ {"role": "user", "content": "Click the sign-in button on the page"} ] inputs = tokenizer.apply_chat_template( messages, tools=tools, enable_thinking=False, add_generation_prompt=True, return_tensors="pt", return_dict=True ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=512, do_sample=False) response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=False) ``` ### Tool Calling Format Use native structured `tool_calls` with dictionary arguments; do not reuse MiniCPM's template or tool serialization. Spark emits `name` with ``/`` fields. For long contexts in production, use a Spark-compatible serving runtime. --- ## Technical Specifications ## Fixed BF16 Routing Results (2026-09-26) | Metric | BF16 Routing Score | |---|---:| | First-turn structured calls | **97/100** | | Strict exact action | **9/89** | | Loose tool-family match | **39/89** | *Evaluated across 100 first turns and 89 scored fixed-history scenarios (11 predetermined skips). Retains five generation timeouts and five discouraged actions in the denominators without cherry-picking.* --- ## License **Noncommercial research only.** This model and its fine-tuned weights are for noncommercial research purposes only. The upstream Spark model/code license is included in `LICENSE`; it does not change this release's usage restriction.