name: gemma-2b results:
- task: type: text-generation dataset: name: Wikitext type: wikitext metrics:
  - type: perplexity (BASELINE) value: 42.85221449187819
  - type: perplexity (BASIC) value: 207.45720773419006

This is a d-Matrix functional reference of the GEMMA-2B model. The reference provides the following functional configurations:

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

Usage

Install d-Matrix Dmx_Compressor first.

pip install dmx_compressor

The following is an example model and its evaluation.

git clone https://github.com/EleutherAI/lm-evaluation-harness
cd lm-evaluation-harness
pip install -e .

python

from dmx.compressor.modeling import DmxModel
import lm_eval

model_args = "pretrained=d-matrix/gemma-2b,trust_remote_code=True"

lm = lm_eval.api.registry.get_model("hf").create_from_arg_string(model_args, {"batch_size": 1})

# Transform the model with DMX
lm._model = DmxModel.from_torch(lm._model)

eval_results = lm_eval.evaluate(lm, lm_eval.tasks.get_task_dict(["wikitext"]))  # Assign desired task, i.e. "wikitext"

RichardErkhov/d-matrix_-_gemma-2b-awq

Original model description:

Usage

RichardErkhov/
d-matrix_-_gemma-2b-awq