Update README.md

README.md

@@ -1,13 +1,83 @@
 ---
-title: Dmx Lm Eval
-emoji: 🐢
-colorFrom: green
-colorTo: blue
+title: DmxMetric
+emoji: 🌖
+colorFrom: purple
+colorTo: pink
 sdk: gradio
 sdk_version: 4.41.0
 app_file: app.py
 pinned: false
 license: apache-2.0
+tags:
+- evaluate
+- metric
+description: >-
+  Evaluation function using lm-eval with d-Matrix integration.
+  This function allows for the evaluation of language models across various tasks, 
+  with the option to use d-Matrix compressed models. For more information, see
+  https://github.com/EleutherAI/lm-evaluation-harness and https://github.com/d-matrix-ai/dmx-compressor
 ---
+# Metric Card for dmxMetric
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+## How to Use
+
+import evaluate
+
+metric = evaluate.load("d-matrix/dmxMetric", module_type="metric")
+
+results = metric._compute(
+    model="d-matrix/gpt2",
+    revision = "distilgpt2",
+    tasks="wikitext",
+    dmx_config = "BASIC" 
+)
+
+print(results)
+
+### Inputs
+- **model** (`str`): The name or path of the model to evaluate.
+- **tasks** (`Union[str, List[str]]`): The task or list of tasks to evaluate on.
+- **dmx_config** (`Optional[str]`): Configuration string for d-Matrix transformations, defaults to None.
+- **num_fewshot** (`Optional[int]`): Number of examples in few-shot context, defaults to None.
+- **batch_size** (`Optional[Union[int, str]]`): Batch size for evaluation, defaults to None.
+- **max_batch_size** (`Optional[int]`): Maximum batch size to try with automatic batch size detection, defaults to None.
+- **limit** (`Optional[Union[int, float]]`): Limit the number of examples per task, defaults to None.
+- **device** (`Optional[str]`): Device to run on, defaults to 'cuda' when available, otherwise 'cpu'.
+- **revision** (`str`): Model revision to use, defaults to 'main'.
+- **trust_remote_code** (`bool`): Whether to trust remote code, defaults to False.
+- **log_samples** (`bool`): If True, logs all model outputs and documents, defaults to True.
+- **verbosity** (`str`): Logging verbosity level, defaults to 'INFO'.
+- **kwargs**: Additional keyword arguments to pass to `lm_eval.evaluate`.
+
+### Output Values
+- **results** (`dict`): A dictionary containing the evaluation results for each task.
+
+Output Example:
+```python
+{
+    'wikitext': {
+        'alias': 'wikitext',
+        'word_perplexity,none': 56.66175009356436,
+        'word_perplexity_stderr,none': 'N/A',
+        'byte_perplexity,none': 2.127521665015424,
+        'byte_perplexity_stderr,none': 'N/A',
+        'bits_per_byte,none': 1.0891738232631387,
+        'bits_per_byte_stderr,none': 'N/A'
+    }
+}
+```
+
+This metric outputs a dictionary containing the evaluation results for each task. In this example, the results are shown for the 'wikitext' task. The output includes various perplexity and bits-per-byte metrics, along with their standard errors (where available). The specific metrics may include:
+
+- `alias`: The name or alias of the task.
+- `word_perplexity,none`: The perplexity calculated on a word level.
+- `word_perplexity_stderr,none`: The standard error of the word perplexity (if available).
+- `byte_perplexity,none`: The perplexity calculated on a byte level.
+- `byte_perplexity_stderr,none`: The standard error of the byte perplexity (if available).
+- `bits_per_byte,none`: The average number of bits required to encode each byte of the text.
+- `bits_per_byte_stderr,none`: The standard error of the bits per byte metric (if available).
+
+Note that 'N/A' values indicate that the standard error was not calculated or not available for that metric.
+
+## Citation(s)
+https://github.com/EleutherAI/lm-evaluation-harness