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nncf.compress_weights with the following parameters:pip install optimum[openvino]from transformers import AutoTokenizer
from optimum.intel.openvino import OVModelForCausalLM
model_id = "OpenVINO/qwen3-0.6b-int8-ov"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = OVModelForCausalLM.from_pretrained(model_id)
inputs = tokenizer("What is OpenVINO?", return_tensors="pt")
outputs = model.generate(**inputs, max_length=200)
text = tokenizer.batch_decode(outputs)[0]
print(text)pip install openvino-genai huggingface_hubimport huggingface_hub as hf_hub
model_id = "OpenVINO/qwen3-0.6b-int8-ov"
model_path = "qwen3-0.6b-int8-ov"
hf_hub.snapshot_download(model_id, local_dir=model_path)
import openvino_genai as ov_genai
device = "CPU"
pipe = ov_genai.LLMPipeline(model_path, device)
pipe.get_tokenizer().set_chat_template(pipe.get_tokenizer().chat_template)
print(pipe.generate("What is OpenVINO?", max_length=200))