amend model card

README.md

@@ -4,4 +4,50 @@ language:
 - en
 base_model:
 - meta-llama/Llama-3.1-8B-Instruct
----
+---
+
+## Introduction
+A predictive weak LLM for translating user chat to a specific transformation task. This model is fine-tuned on a curated training dataset that collects common transformation tasks in the wild.
+
+Users can interact with the model via 1) direct chat; 2) providing example pairs; 3) describing patterns or mixed input.
+
+This model will predict the most suitable task and return operator & coding instructions accordingly.
+
+This model can classify the following data transformation tasks:
+1. Format: related to value consistency without arithmetic relation, e.g., to lower case, ABC → abc.
+2. UnitConvert: transform regular metrics using a range of measurement unit scales, e.g., Hour → Minute, Kilogram→ Pound.
+3. Extract: generally driven by Regex, e.g., ABC → BC.
+4. DomainCalculate: convert cross-domain value by calculation, often observed in numerics, e.g., Unix timestamp → Local time with timezone.
+5. DomainMap: convert cross-domain value by mapping relation, often observed in categorical case, e.g., Color RGB → Hex.
+6. Transform: default, if none of the above all
+
+---
+## Examples
+User chat + example-pair
+
+- Unit Conversion
+
+```
+### Instruction ###
+kgs to pounds, one digit after the decimal, rounding
+
+### Examples ###
+Input: 2
+Output: 4.4
+Input: 3
+Output: 6.6
+```
+unit_convert(): Convert kilograms to pounds, rounding to one decimal place
+
+- Month number to name
+```
+### Instruction ###
+convert month number to month name
+
+### Examples ###
+Input: 7
+Output: July
+Input: 12
+Output: December
+```
+domain_map(): Convert a month number to its corresponding month name.