Piccolo
Collection
12 items β’ Updated
How to use agentscope-ai/Piccolo-9B with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="agentscope-ai/Piccolo-9B") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM
processor = AutoProcessor.from_pretrained("agentscope-ai/Piccolo-9B")
model = AutoModelForMultimodalLM.from_pretrained("agentscope-ai/Piccolo-9B", device_map="auto")Piccolo-9B is a decision model for tool review and context selection. This repository contains the complete Safetensors checkpoint.
hf download agentscope-ai/Piccolo-9B --local-dir Piccolo-9B
Use the included reference implementation for bidirectional attention and candidate scoring.
python -m pip install -r Piccolo-9B/requirements.txt
python Piccolo-9B/piccolo_inference.py --model Piccolo-9B --request request.json --device cuda:0
Use the request example to prepare request.json.
Use Piccolo locally for tool review and context selection with the QwenPaw setup guide.
| HarnessJevBench Hard β | DataJevBench β | JevBench Public β | Decision Index Public β |
|---|---|---|---|
| 68.81% | 69.40% | 89.61% | 60.86 |
Benchmark results are for the full checkpoint.
This model is also available on ModelScope.
Base model
Qwen/Qwen3.5-9B-Base