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Adonis3039
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Model Details
Model Provider
Adonis3039
Model Tree
Qwen/Qwen3-8B
Input Modalities
Output Modalities
Supported Functionality
adapter_model.safetensors: complete learned LoRA parameters (rank 32).adapter_config.json: portable PEFT configuration with the public base-model ID.metadata/training_audit.json: canonical-target and repair-row audit.metadata/leakage_report.json: source/task/claim isolation audit.release_manifest.json: checksum and explicit release boundary.python
from transformers import AutoModelForCausalLM, AutoTokenizerfrom peft import PeftModelbase_id = "Qwen/Qwen3-8B"tokenizer = AutoTokenizer.from_pretrained(base_id, trust_remote_code=True)base = AutoModelForCausalLM.from_pretrained(base_id, device_map="auto")model = PeftModel.from_pretrained(base, "/path/to/EviWeave-VisualPlanner-8B")model.eval()
The canonical VisualPlan prompt/compiler and verifier are in the separate code package. This adapter is intended for structured visual planning, not as a stand-alone factual extractor or general report writer. Generated plans must still pass deterministic schema, grounding, fidelity, and rendering checks.
The planner used 6,904 first-stage SFT examples over 2,040 source-disjoint tasks (5,399 final-plan and 1,505 verifier-passing repair rows), followed by a 1,920-example Boundary SFT stage (480 final-plan and 1,440 repair rows).
The package omits training data, trainer state, merged weights, and external API models. It therefore supports inference and model inspection but not complete training reproduction during peer review.