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d-matrix/
gpt2-large

Name: gpt2-large
Availability: InStock

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This is a d-Matrix functional reference of the GPT2-LARGE 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`

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
from lm_eval.models.huggingface import HFLM

lm_eval.api.registry.register_model("hf", HFLM)
model_args = "pretrained=d-matrix/gpt2-large,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"