metadata
license: apache-2.0
base_model: Qwen/Qwen2.5-3B-Instruct
tags:
- lora
- sysbreak
- event-generation
- qwen2.5
- cyberpunk
library_name: peft
sysbreak-grid-runner-lora
LoRA adapter for SYSBREAK event generation (Qwen2.5-3B-Instruct base)
Model Details
- Base Model: Qwen/Qwen2.5-3B-Instruct
- Fine-tuning Method: LoRA (Low-Rank Adaptation)
- Model Type: Causal Language Model
- Language: English
- License: Apache 2.0
- Use Case: GRID-RUNNER content generation for SYSBREAK cyberpunk game
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
# Load base model
base_model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen2.5-3B-Instruct",
device_map="auto",
torch_dtype="auto"
)
# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "nullvektordom/sysbreak-grid-runner-lora")
tokenizer = AutoTokenizer.from_pretrained("nullvektordom/sysbreak-grid-runner-lora")
# Generate
prompt = "Generate cyberpunk content"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Project
Part of SYSBREAK - A cyberpunk terminal-based game.