---
license: apache-2.0
datasets:
- wikitext
- ptb_text_only
language:
- en
metrics:
- perplexity
pipeline_tag: text-generation
model-index:
- name: distilgpt2
  results:
  - task:
      type: text-generation
    dataset:
      name: penn_treebank
      type: ptb_text_only
    metrics:
    - name: perlexity@distilgpt2:BASELINE
      type: dmx-perlexity
      value: 63.45857238769531
    - name: perlexity@distilgpt2:BASIC
      type: dmx-perlexity
      value: 64.36720275878906
  - task:
      type: text-generation
    dataset:
      name: wikitext2
      type: wikitext-2-raw-v1
    metrics:
    - name: perlexity@distilgpt2:BASELINE
      type: dmx-perlexity
      value: 46.05925369262695
    - name: perlexity@distilgpt2:BASIC
      type: dmx-perlexity
      value: 46.570838928222656
---
This is a d-Matrix functional reference of the GPT2 model family, with the following *revisions*: 
- [`distilgpt2`](https://huggingface.co/distilbert/distilgpt2)
- [`gpt2`](https://huggingface.co/openai-community/gpt2)
- [`gpt2-medium`](https://huggingface.co/openai-community/gpt2-medium) 
- [`gpt2-large`](https://huggingface.co/openai-community/gpt2-large) 
- [`gpt2-xl`](https://huggingface.co/openai-community/gpt2-xl)

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 `BFP16-64`, and all other operations transformed to approximated kernel simulations


### Usage

Install d-Matrix [ML Tools](https://github.com/d-matrix-ai/dmx-mltools) first.

```sh
pip install dmx-mltools
```

The following is an example model and its evaluation.  

```python
from mltools.dmx import pipeline

pipe = pipeline(
    task="text-generation",
    model="d-matrix/gpt2",
    revision="gpt2-xl",  # see above for other variants
    dmx_config="BASELINE",  # see above for other variants
    trust_remote_code=True,
    # device_map="auto",  # enabling model parallel on multi-GPU nodes
)

results = pipe.evaluate(metric="d-matrix/perplexity", dataset="wikitext-2")
```

### Evaluation results

- `perplexity` on `penn_treebank`
  Revision \ Configuration | **`BASELINE`** | **`BASIC`** 
  :-- | --: | --: 
  `distilgpt2` | - | - 'loss': 4.150386810302734, 'perplexity': 63.45854187011719
  `gpt2` | - | -
  `gpt2-medium` | - | -
  `gpt2-large` | - | -
  `gpt2-xl` | - | -

- `perplexity` on `wikitext2`
  Revision \ Configuration | **`BASELINE`** | **`BASIC`** 
  :-- | --: | --:
  `distilgpt2` | - | -
  `gpt2` | - | -
  `gpt2-medium` | - | -
  `gpt2-large` | - | -
  `gpt2-xl` | - | -