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Quantization Parameters

Weight compression was performed using nncf.compress_weights with the following parameters:

Compatibility

The provided OpenVINO™ IR model is compatible with:

  • OpenVINO version 2024.1.0 and higher
  • Optimum Intel 1.16.0 and higher

Running Model Inference

  1. Install packages required for using Optimum Intel integration with the OpenVINO backend:
pip install optimum[openvino]
  1. Run model inference:
from transformers import AutoTokenizer
from optimum.intel.openvino import OVModelForCausalLM

model_id = "El-chapoo/qwen2_0.5B_8_int8.ov"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = OVModelForCausalLM.from_pretrained(model_id)

inputs = tokenizer("def print_hello_world():", return_tensors="pt")

outputs = model.generate(**inputs, max_length=200)
text = tokenizer.batch_decode(outputs)[0]
print(text)

For more examples and possible optimizations, refer to the OpenVINO Large Language Model Inference Guide.

Legal information

Disclaimer

Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See Intel’s Global Human Rights Principles. Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights.

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