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examples/llm_compression/openvino/smollm2_360m_fp8
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# limitations under the License.
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from functools import partial
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- import datasets
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import numpy as np
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import openvino as ov
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+ from datasets import load_dataset
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from optimum .intel .openvino import OVModelForCausalLM
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from transformers import AutoTokenizer
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@@ -75,7 +75,7 @@ def main():
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MODEL_ID = "HuggingFaceTB/SmolLM2-360M-Instruct"
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OUTPUT_DIR = "smollm2_360m_compressed"
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- dataset = datasets . load_dataset ("wikitext" , "wikitext-2-raw-v1" , split = "test" )
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+ dataset = load_dataset ("wikitext" , "wikitext-2-raw-v1" , split = "test" )
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# Filtering to remove empty samples from the dataset
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dataset = dataset .filter (lambda example : len (example ["text" ]) > 1 )
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openvino == 2024.5
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optimum-intel [openvino ]
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transformers
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- onnx < 1.16.2
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+ onnx == 1.17.0
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