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README.md
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Configuration | Explanation
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:-- | :--
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**`BASELINE`** | a reference functionally equivalent to the original model
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**`BASIC`** | all linear algebraic operands quantized to `MXINT8-64
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### Usage
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```python
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from dmx.compressor.modeling import DmxModel
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import lm_eval
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model_args = "pretrained=d-matrix/gpt2-medium,trust_remote_code=True"
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lm = lm_eval.api.registry.get_model("hf").create_from_arg_string(model_args, {"batch_size": 1})
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Configuration | Explanation
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:-- | :--
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**`BASELINE`** | a reference functionally equivalent to the original model
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**`BASIC`** | all linear algebraic operands quantized to `MXINT8-64`
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### Usage
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```python
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from dmx.compressor.modeling import DmxModel
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import lm_eval
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from lm_eval.models.huggingface import HFLM
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lm_eval.api.registry.register_model("hf", HFLM)
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model_args = "pretrained=d-matrix/gpt2-medium,trust_remote_code=True"
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lm = lm_eval.api.registry.get_model("hf").create_from_arg_string(model_args, {"batch_size": 1})
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