metadata
model-index:
- 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 .
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).to_basic_model() # Using BASIC configuration
eval_results = lm_eval.evaluate(lm, lm_eval.tasks.get_task_dict([task])) # Assign desired task, i.e. "wikitext"