Text Generation
PEFT
Safetensors
lora
visual-planning
provenance
report-generation
peer-review-artifact
Instructions to use Adonis3039/EviWeave-VisualPlanner-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Adonis3039/EviWeave-VisualPlanner-8B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B") model = PeftModel.from_pretrained(base_model, "Adonis3039/EviWeave-VisualPlanner-8B") - Notebooks
- Google Colab
- Kaggle
| { | |
| "name": "EviWeave-VisualPlanner-8B", | |
| "release_scope": "complete adapter; base and merged weights excluded", | |
| "base_model": "Qwen/Qwen3-8B", | |
| "peft_type": "LoRA", | |
| "rank": 32, | |
| "lora_alpha": 64, | |
| "lora_dropout": 0.05, | |
| "adapter_bytes": 349243752, | |
| "adapter_sha256": "e2b25e761d2cf25fb9cbc5a3b63f7098ae33fef17587574350127685e096f7fb", | |
| "original_frozen_adapter_sha256": "e2b25e761d2cf25fb9cbc5a3b63f7098ae33fef17587574350127685e096f7fb", | |
| "excluded": [ | |
| "Qwen3-8B base weights", | |
| "16 GB merged checkpoint", | |
| "optimizer/trainer state", | |
| "training corpus", | |
| "deployment logs", | |
| "provider credentials" | |
| ] | |
| } | |