Views
No views yet
| Configuration | Explanation |
|---|---|
BASELINE | a reference functionally equivalent to the original model |
BASIC | all linear algebraic operands quantized to MXINT8-64, and all other operations transformed to approximated kernel simulations |
pip install dmx_compressor1git clone https://github.com/EleutherAI/lm-evaluation-harness
2cd lm-evaluation-harness
3pip install -e .1from dmx.compressor.modeling import DmxModel
2import lm_eval
3
4model_args = "pretrained=d-matrix/gemma-2b,trust_remote_code=True"
5
6lm = lm_eval.api.registry.get_model("hf").create_from_arg_string(model_args, {"batch_size": 1})
7
8# Transform the model with DMX
9lm._model = DmxModel.from_torch(lm._model)
10
11eval_results = lm_eval.evaluate(lm, lm_eval.tasks.get_task_dict(["wikitext"])) # Assign desired task, i.e. "wikitext"