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onevloth/pc-agent-dispatcher-gemma4-e2b
pc-agent-dispatcher-gemma4-e2b is a text generation model from onevloth. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as gemma.
A LoRA adapter that turns Gemma 4 E2B into the dispatcher (router) for PC-Agent: it reads a natural-language request and emits one JSON tool-call for controlling a Windows PC.
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From the Hugging Face model README
A LoRA adapter that turns Gemma 4 E2B into the dispatcher (router) for PC-Agent: it reads a natural-language request and emits one JSON tool-call for controlling a Windows PC.
{"action": "tool", "tool": "open_app", "args": {"app": "notepad"}}
{"action": "plan", "steps": [{"tool": "open_app", "args": {"app": "notepad"}},
{"tool": "type_text", "args": {"text": "hello"}}]}
{"action": "chat"}
🔗 Full project, desktop app, and demos on GitHub: github.com/AlfatihRabbani/pc-agent
git clone https://github.com/AlfatihRabbani/pc-agent
cd pc-agent
scripts\setup.bat :: venv + CUDA torch + deps
python scripts\download_models.py :: base E2B (~10 GB)
.venv\Scripts\hf download onevloth/pc-agent-dispatcher-gemma4-e2b --local-dir models\dispatcher-final
PC-Agent.vbs :: launch the desktop app
Full instructions (incl. the optional 12B chat model via Ollama) are in the repo README.
huihui-ai/Huihui-gemma-4-E2B-it-abliterated (load in 4-bit / NF4).import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
from peft import PeftModel
base = "huihui-ai/Huihui-gemma-4-E2B-it-abliterated"
q = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.bfloat16, bnb_4bit_use_double_quant=True)
tok = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, quantization_config=q, device_map="auto")
model = PeftModel.from_pretrained(model, "onevloth/pc-agent-dispatcher-gemma4-e2b")
Derivative of Google Gemma 4 — governed by the Gemma Terms of Use. The PC-Agent code is MIT.