add local perplexity

README.md

@@ -1,50 +1,19 @@
----
-title: local_perplexity
-datasets:
--  
-tags:
-- evaluate
-- metric
-description: "TODO: add a description here"
+title: Perplexity
+emoji: 🤗
+colorFrom: blue
+colorTo: red
 sdk: gradio
 sdk_version: 3.19.1
 app_file: app.py
 pinned: false
----
-
-# Metric Card for local_perplexity
-
-***Module Card Instructions:*** *Fill out the following subsections. Feel free to take a look at existing metric cards if you'd like examples.*
-
-## Metric Description
-*Give a brief overview of this metric, including what task(s) it is usually used for, if any.*
-
-## How to Use
-*Give general statement of how to use the metric*
-
-*Provide simplest possible example for using the metric*
-
-### Inputs
-*List all input arguments in the format below*
-- **input_field** *(type): Definition of input, with explanation if necessary. State any default value(s).*
-
-### Output Values
-
-*Explain what this metric outputs and provide an example of what the metric output looks like. Modules should return a dictionary with one or multiple key-value pairs, e.g. {"bleu" : 6.02}*
-
-*State the range of possible values that the metric's output can take, as well as what in that range is considered good. For example: "This metric can take on any value between 0 and 100, inclusive. Higher scores are better."*
-
-#### Values from Popular Papers
-*Give examples, preferrably with links to leaderboards or publications, to papers that have reported this metric, along with the values they have reported.*
-
-### Examples
-*Give code examples of the metric being used. Try to include examples that clear up any potential ambiguity left from the metric description above. If possible, provide a range of examples that show both typical and atypical results, as well as examples where a variety of input parameters are passed.*
-
-## Limitations and Bias
-*Note any known limitations or biases that the metric has, with links and references if possible.*
-
-## Citation
-*Cite the source where this metric was introduced.*
-
-## Further References
-*Add any useful further references.*
+tags:
+  - evaluate
+  - metric
+description: >-
+  Perplexity (PPL) is one of the most common metrics for evaluating language
+  models. It is defined as the exponentiated average negative log-likelihood of
+  a sequence, calculated with exponent base `e`.
+
+  For more information on perplexity, see [this
+  tutorial](https://huggingface.co/docs/transformers/perplexity).
+Metric Card for Perplexity