Update README.md

README.md

@@ -30,5 +30,65 @@ configs:
     path: data/train-*
 ---
 # Dataset Card for "databricks-dolly-15k-chatml"
+## Dataset Summary
+This dataset has been created by **Re:cast AI** to transform the existing dataset [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) into a [chatml](https://huggingface.co/docs/transformers/main/en/chat_templating) friendly format for use in SFT tasks with pretrained models.
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+
+## Dataset Structure
+```python
+messages = [
+  { "content": "You are an expert Q&A system that is trusted around the world. You always... etc.", "role": "system" }, 
+  { "content": "(Optional) Context information is below.\n----------------\nVirgin Australia, the... etc.", "role": "user" }, 
+  { "content": "Virgin Australia commenced services on 31 August 2000... etc.", "role": "assistant" } ]
+]
+```
+
+## Usage
+```python
+from datasets import load_dataset
+dataset = load_dataset("recastai/databricks-dolly-15k-chatml", split="train")
+```
+
+## Processing applied to original dataste
+```python
+INSTRUCTIONS = """You are an expert Q&A system that is trusted around the world. You always answer the user's query in a helpful and friendly way.
+Some rules you always follow:
+1. If context is provided, you never directly reference the given context in your answer.
+2. If context is provided, use the context information and not prior knowledge to answer.
+3. Avoid statements like 'Based on the context, ...' or 'The context information ...' or 'The answer to the user's query...' or anything along those lines.
+4. If no context is provided use your internal knowledge to answer."""
+
+# databricks-dolly-15k features:
+# - instruction: The user query/question
+# - context: (optional) context to use to help the assistant
+# - response: The assistant's response to the query/question
+#
+key_mapping = dict(
+    query = "instruction",
+    context = "context",
+    response = "response"
+)
+
+def process_chatml_fn(example, validation=False):
+    """
+    Processing specific to databricks-dolly-15k into a chat format.
+    """
+    user_content = (
+        "(Optional) Context information is below.\n"
+        "----------------\n"
+        "{context}\n"
+        "----------------\n"
+        "Answer the following query.\n"
+        "{query}\n"
+    )
+    assistant_content = "{response}"
+    
+    message = [
+        {"role": "system", "content": INSTRUCTIONS},
+        {"role": "user", "content": user_content.format(context=example[key_mapping['context']], query=example[key_mapping['query']])},
+        {"role": "assistant", "content": assistant_content.format(response=example[key_mapping['response']])} 
+    ]
+
+    return message
+```