Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,51 @@
+---
+model-index:
+- name: opt-6b7
+  results:
+  - task:
+      type: text-generation
+    dataset:
+      name: Wikitext
+      type: wikitext
+    metrics:
+    - type: perplexity (BASELINE)
+      value: 12.286456082558505
+    - type: perplexity (BASIC)
+      value: 12.300496271519869
+---
+This is a d-Matrix functional reference of the OPT-6B7 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](https://github.com/d-matrix-ai/dmx-compressor) first.
+```sh
+pip install dmx_compressor
+```
+
+The following is an example model and its evaluation.
+
+```sh
+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/opt-6b7,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"
+```